To my parents, for all they sacrificed to provide me the … · 2012-10-04 · 4 ACKNOWLEDGMENTS First and foremost, I thank my chair, Dr. Andres Blanco, for inspiring me to think

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LOCAL ECONOMIC IMPACTS OF AIRPORT OPERATIONS: AN ECONOMIC IMPACT ASSESSMENT FOR THE WEST ORANGE AIRPORT

AUTHORITY

By

GARETH REECE HANLEY

A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT

OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN URBAN AND REGIONAL PLANNING

UNIVERSITY OF FLORIDA

2012

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© 2012 Gareth Reece Hanley

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To my parents, for all they sacrificed to provide me the opportunity to become a scholar

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ACKNOWLEDGMENTS

First and foremost, I thank my chair, Dr. Andres Blanco, for inspiring me to think

like an economist. The world is different when you accept the adage “there is no such

thing as a free lunch.” I also thank my co-chair, Dr. Ruth Steiner, who opened my eyes

to the different aspects of transportation planning. Without their guidance this thesis

would not have been possible.

I thank my family and friends for their continued support through this process. My

mom and dad have always been very supportive of all my academic endeavors and this

thesis was no different. My thesis buddy, Brittany McMullen, has been very supportive

and encouraging throughout the development of this document. I am also thankful to

have been in the supportive company of Ivelisse, Caitlin, Lara, and Brett when working

on the final portions of my thesis.

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TABLE OF CONTENTS page

ACKNOWLEDGMENTS................................................................................................. 4

LIST OF TABLES........................................................................................................... 8

LIST OF FIGURES ...................................................................................................... 10

LIST OF ABBREVIATIONS .......................................................................................... 11

ABSTRACT.................................................................................................................. 12

CHAPTER

1 INTRODUCTION ................................................................................................... 14

Problem Statement ................................................................................................ 14

Research Questions and Objectives ...................................................................... 15

Method .................................................................................................................. 15

2 LITERATURE REVIEW ......................................................................................... 17

Barriers and Limitations to Airport Prosperity ......................................................... 17

The Rise of the Aerotropolis .................................................................................. 20

Benefits of the Airport in the Community ................................................................ 24

Economic Principles of Air Transportation ............................................................. 27

Summary ............................................................................................................... 28

3 DESCRIPTION OF STUDY AREA ........................................................................ 30

Orange County Economic Profile ........................................................................... 30

Demographics ................................................................................................. 30

Business Establishments ................................................................................ 32

Transportation Assets ..................................................................................... 33

State Road 429 Extension Corridor ....................................................................... 34

West Orange Airport Authority ............................................................................... 37

Orlando Apopka Airport Profile ........................................................................ 37

Bob White Field Profile .................................................................................... 39

Orlando North Airpark Profile .......................................................................... 39

Proposed Airport Development ....................................................................... 40

Conceptual plans ...................................................................................... 41

Estimated expenditure outlook .................................................................. 43

4 ECONOMIC BASE ANALYSIS METHODOLOGY AND RESULTS ....................... 45

North American Industry Classification System Overview ...................................... 45

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Employment Dynamics .......................................................................................... 47

Location Quotient Analysis .................................................................................... 48

Analysis Overview ........................................................................................... 48

Analysis Results .............................................................................................. 50

Shift-Share Analysis .............................................................................................. 51



Economic growth ...................................................................................... 54

Mix shift .................................................................................................... 55

Competitive shift ....................................................................................... 56

Esteban-Marquillas Extension ............................................................................... 56



Summary ............................................................................................................... 60

5 INPUT-OUTPUT ANALYSIS METHODOLOGY AND RESULTS ........................... 61

Analysis Overview ................................................................................................. 61

IMPLAN Software ............................................................................................ 62

Construction Costs .......................................................................................... 63

Operational Costs ........................................................................................... 63

Analysis Results .................................................................................................... 64

Multiplier Coefficients ...................................................................................... 64

Construction Scenarios ................................................................................... 66

2015 Airport Operations Scenarios ................................................................. 66




Top 10 Affected Industries .............................................................................. 70

Summary ............................................................................................................... 70

6 CLUSTER ANALYSIS METHODOLOGY AND RESULTS ..................................... 73

Analysis Overview ................................................................................................. 73

Analysis Results .................................................................................................... 74

7 DISCUSSION OF RESULTS ................................................................................. 77

Support Activities for Air Transportation Sector ..................................................... 77

Nonscheduled Air Transportation Sector ............................................................... 80

Economic Impacts ................................................................................................. 81

Most Affected Industries ........................................................................................ 83

Clustered Industries ............................................................................................... 84

Summary ............................................................................................................... 85

8 CONCLUSION ...................................................................................................... 86

Recommendations ................................................................................................. 86

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Limitations ............................................................................................................. 86

Opportunities for Future Research ......................................................................... 87

Final Thoughts ....................................................................................................... 88

APPENDIX

A PROJECTED AIRPORT CONSTRUCTION AND OPERATIONAL BUDGETS ...... 90

B NAICS INDUSTRY SECTOR DEFINITIONS ......................................................... 94

LIST OF REFERENCES .............................................................................................. 96

BIOGRAPHICAL SKETCH ........................................................................................... 99

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LIST OF TABLES

Table page 3-1 Top 5 Orange County Industry Sectors, by Employment ................................... 33

4-1 2005-2010 Employment .................................................................................... 48

4-2 Location Quotient Values and Corresponding Conclusions ............................... 50

4-3 Location Quotient Results ................................................................................. 51

4-4 2005-2010 Shift-Share Results for Orange County to Florida ............................ 54

4-5 2005-2010 Shift-Share Results for Orange County to United States ................. 54

4-6 Esteban Marquillas Extension 2005-2010 Orange County to Florida ................. 59

4-7 Esteban Marquillas Extension 2005-2010 Orange County to United States ...... 59

5-1 Study Area Multiplier Coefficients ...................................................................... 65

5-2 Construction Scenario Impact Summary for SR 429 Ext. Corridor ..................... 67

5-3 Construction Scenario Impact Summary for Orange County ............................. 67

5-4 2015 Airport Operations Scenario Impact Summary for SR 429 Ext. Corridor ... 67

5-5 2015 Airport Operations Scenario Impact Summary for Orange County ............ 67







5-12 Top 10 Affected Industries for Airport Operations by Output in SR 429 Ext. Corridor ............................................................................................................. 71

5-13 Top 10 Affected Industries for Airport Operations by Output in Orange County ............................................................................................................... 72

6-1 LQ Values for Industries Most Affected by Airport Operations ........................... 74

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A-1 Preliminary Cost Estimate of Total Project and Phasing .................................... 91

A-2 Abridged Near Term and Long Term Operation Revenue/Cost Estimates With Assumptions.............................................................................................. 93

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LIST OF FIGURES

Figure page 3-1 Map of Orange County Study Area .................................................................... 31

3-2 Map of Orange County Transportation Infrastructure......................................... 35

3-3 Map of SR 429 Extension Corridor Study Area .................................................. 36

6-1 Location of Potential Industry Clusters Map ...................................................... 76

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LIST OF ABBREVIATIONS

BLS Bureau of Labor Statistics

FAA Federal Aviation Administration

FASP Florida Aviation System Plan

FDOT Florida Department of Transportation

GDP Gross Domestic Product

GIS Geographic Information System

IMPLAN Impact Analysis for Planning

JIT Just in Time

LEHD Longitudinal Employer-Household Dynamics

LQ Location Quotient

NAICS North American Industry Classification System

SR State Road

WOAA West Orange Airport Authority

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the

Requirements for the Degree of Master of Arts in Urban and Regional Planning

LOCAL ECONOMIC IMPACTS OF AIRPORT OPERATIONS: AN ECONOMIC IMPACT ASSESSMENT FOR THE WEST ORANGE AIRPORT

AUTHORITY

By

Gareth Reece Hanley

May 2012

Chair: Andres Blanco Co-chair: Ruth Steiner Major: Urban and Regional Planning

Over the last decade, airports and aviation industries have suffered from the

perception of an unhealthy and unnecessary industry. This is due to arguments about

industry safety and economic sustainability. The goal of this research is to debunk some

of the negative perceptions of airports and. to show that airport growth is not only a

good thing but public investment in the industry is justified. A case study of airport

development plans in Orange County, Florida shows that significant economic benefits

can come from public investment in airport development. Analysis shows that airport

related operations in Orange County are not only specialized but also hold a

comparative advantage over the industry at the state and national level. These results

indicate the health of the local industry while the overall national employment suffers.

With the help of a line item budget from a feasibility study, local economic impacts

of construction and annual airport operations were quantified. As is the case with any

major infrastructure development, the regional economy is positively impacted as

construction activities are conducted. Analysis also shows that positive economic

effects could be the result of the annual airport operations. To substantiate the

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sustainability of airport operations, a cluster analysis was conducted to identify

possibilities for industry clusters in the area. Results showed that clustering will only

serve to increase the local economic impact of airport operations; further justifying the

large public investment.

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CHAPTER 1 INTRODUCTION

Problem Statement

In a time when government expenditures are publically scrutinized, more than ever

public investment must be justified. The public wants to know that their tax dollars are

being put to the highest and best use to serve the greater good. In some cases,

Investment in airports often becomes a hot-button issue because of the many concerns

of the public.

It would be difficult to imagine modern life without the ability to get on an airplane

and travel to a faraway destination in a relatively short amount of time. Despite this,

airport growth can often be stifled because of skeptics. Everything from airport noise,

aviation safety, and industry economic stability are brought up as arguments against

airport growth (Hakfoort, Poot, & Rietveld, 2001; McMillen, 2004). Ever since the

terrorist attacks of September 11, 2001, the aviation industry has been scrutinized for its

safety. These perceptions hurt the industry as airlines became defunct and others

merged to stave off bankruptcy. Concerns about the health of the aviation industry are

common. Some think that it is a dying industry because of the unsustainable operational

costs. This is especially poignant as oil-based fuel prices have been increasing in recent

years.

It is important to remember that despite the negative attributes associated with

airport operations (i.e., aircraft noise); air travel has become an integral part of our way

of life. To sustain the current standard of living, airports and aviation must be

maintained as a prominent method of transporting goods and people over long

distances.

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Increasingly, airports are being heralded as economic growth engines. No longer

are airports simply another transportation hub. Economic activity around some airports

is increasing so much that they are themselves being equated to cities. A growing trend

is for airport related firms to locate on or very near airport property. The debate raises

the question should airport growth be encouraged as their importance is being

recognized?

Research Questions and Objectives

State and federal agencies are planning to invest in airport development in west

Orange County in Florida. The purpose of this research is to determine the economic

impact of airport development in west Orange County. Therefore, the research

questions are as follows:

Is public investment in airport development in Orange County a justified expenditure?

What will be the economic impacts of this development?

Are the economic impacts likely to be sustained?

This researcher hypothesizes that not only will the public investment be a justified

expenditure, but also that it will be followed by significant and sustained economic

benefits.

Method

To answer the research questions, three quantitative analyses are conducted.

Economic base analysis is conducted using three different techniques (location

quotient, shift-share, and Esteban-Marquillas Extension) to determine whether the

airport development project is a worthy investment of taxpayer dollars. An input-output

analysis is used to quantify the economic effects of the development. Finally, a cluster

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analysis is used to determine the economic sustainability of the impacts. Prior to

describing the specifics of how each technique is used in this analysis, pertinent

aviation industry background and economic principles are described in the next chapter.

Chapter 3 describes the study area for this research. Chapter 4 explains the

methodology and analysis results for the economic base analysis. Chapter 5 explains

the methodology and results of the input-output analysis. The methodology and results

for the cluster analysis is described in Chapter 6. Chapter 7 is the discussion of all the

results and conclusions are made in Chapter 8.

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CHAPTER 2 LITERATURE REVIEW

Airports, much like other kinds of ports, create a link for interregional trading and

travel. The positive benefits from airport development and expansion do not simply

include the employment increase but also the effects on demand and supply of the non-

transportation sector of the economy (Hakfoort et al., 2001, p. 597). “Airport act not only

as a hub for human movement and its immediate ancillaries, but also an industrial focus

around which massive conurbations and concomitant support services will be located”

(Charles, Barnes, Ryan, & Clayton, 2007, p. 1009-1010).

Barriers and Limitations to Airport Prosperity

Many countries face the debate about the tradeoff between the positive and

negative impacts of airport expansions. Some people believe that the current negative

impacts from current airport operations provide enough reason to settle the debate

about airport development and increased aviation activity. The list of concerns includes

aviation noise and concerns about safety (Hakfoort et al., 2001).

The attacks on September 11th, 2001 changed how the United States viewed

safety of the airline industry forever. The subsequent negative perception of industry

safety combined with the economic slow-down in the mid 2000’s created reason for

concern for some invested in the industry. After the industry was able to stabilize, the

Federal Aviation Administration (FAA) forecast a steady, 3.3% growth (as measured by

number enplanements) for large U.S. air carriers through 2013 and 5.5% growth for

regional and commuter airlines during the same time (Vasigh, Fleming, & Tacker,

2008).

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A long-standing perception exists that the presence of airports depresses property

values because of noise associated with airport operations. However, research, in

which the author examined real estate records for study areas in six cities (Chicago; Los

Angeles; Denver; Dallas; Newark, New Jersey; and New York City), shows that property

values do not appear to be adversely affected by the presence of airports (Walther,

1953). When compared to other areas of a city, real estate in sections of towns near

airports have a proportionately lower rate of sale listing. The research also showed

proportionally similar sale prices in areas near the airport compared to the rest of the

study area (Walther, 1953).

Herman Walther (1953) provides a personal anecdote of when he lived near an

airport. He remembers hearing airplanes land the first few nights of living near a runway

then eventually to not hearing them at all. He equates this experience to the more

commonly referenced anecdote of living near railroad tracks; residents get used to the

overwhelming amount of sound even though pictures on the wall shake when a train

passes by.

This may not be the same experience with everyone as some people are more

sensitive to auditory stimuli. Luckily, airports are becoming significantly quieter over

time. Technology has allowed new airplanes to be quieter than older planes. Older

aircraft are being retired and the amount of night flights are also being reduced

(McMillen, 2004).

The ‘not in my backyard’ sentiment is often a hindrance to development, of all

sorts. The sentiment also applies to airport development; “for every business leader

who wants to see his or her local airport expand, there is a resident in the flight path of

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an airport who wants to see his or her local airport’s traffic capped” (Green, 2007, p. 91-

92). Another reason that residents may dissent with the idea of expanding airport

operations may be the local residents often feel excluded from the planning process

when it comes to airport development (McMillen, 2004).

Airport development progresses despite the concerns of the critics. Eighteen of the

31 largest airports in the nation (which account for 70% of all US air passenger traffic)

have plans to add runways in the next decade (McMillen, 2004, p. 628). If noise was a

discouraging factor as touted by the critics, then development around airports would not

exist. However, research provides evidence of residential encroachment on airport

properties. Walther (1953) found that there was significant residential construction on

vacant land immediately adjacent airport properties. Suffice it to say that the opponent

argument of damaging effects of airport noise is debunked. The presence of residences

and other developments in the close proximity proves that airport noise and safety

concerns are bearable aspect of airport operations. The encroaching development

toward airports illustrates that airports are a growth node in their respective localities.

Central place theory describes the situation where a growth node (i.e., airports)

attracts smaller firms to a specific location. The smaller firms are drawn to the growth

node because they provide goods and/or services that support and are supported by

the airport (Blakely & Leigh, 2010). Air-based transportation is the fastest method to

transport people and goods around the world so airports certainly provide a very

specific and specialized service. Therefore, their presence in the locality is often

coveted. Central place theory is usually used to describe urban growth to a downtown

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area but, in recent decades, it has also been used to describe the affect airports have

on a locality.

The Rise of the Aerotropolis

With the growing interest of the economic advantages of airports and aviation-

related developments, academics like John Kasarda are getting more attention for their

research. He is one of the most published academics in the area of aviation planning.

He is also credited with the coining of the term ‘aerotropolis,’ Which is an urban form

whose layout is centered on an airport (Kasarda & Lindsay, 2011).

The aerotropolis concept relies on the assumption that airports will overtake

seaports and rail as the primary trading hubs in our cities. Shades of this can be seen

with the advent of just-in-time (JIT) logistics. More than transportation by road, rail, and

sea, airports are becoming more important assets in the logistics and distribution of

goods (Charles et al., 2007).

Air travel is increasingly being used to transport freight nationally and

internationally (Başar & Bhat, 2004). The JIT business model is the driving factor the

use of air travel as the method of delivery. Aviation provides a level of speed and

flexibility that cannot be achieved with any other mode of transportation. When fast

delivery is the most important variable, logistics is important to firms and it is not an

input that is sacrificed or minimized (Flores-Fillol & Nicolini, 2006). However, it is worth

noting that it does not make sense for all goods to be shipped via air. Some goods, like

bulky items, are more economically shipped by sea or rail (Charles et al., 2007). In

these cases, speed must be sacrificed for the lack of better options.

Physical goods are not the only high valued products that are transported though

airports. To an extent, airports also serve as hubs for transporting ‘human capital’ – the

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movement of people and their intellectual property or more simply referred to as

business-related travel. As aircraft are the fastest form of long-range transportation,

business travelers often find this mode of transportation to be most convenient when it

comes to interregional and intercontinental travel. From August 2008 to July 2009, 48%

of U.S. adult air travelers took trips for business purposes as compared to only 42%

traveling for leisure purposes during the same time period. The remaining 10% traveled

because of a combination of business and leisure (U.S. Travel Association, 2011).

Some argue that technological advances associated with new methods of

communication will eventually render travel non-essential. However, academic research

debunks this theory; in fact, the growing ease of communication may be the cause of

travel. Research shows that telecommunication advancements have increased demand.

The rationale is that air travel creates long distance relationships and opportunities that

at some point require travel (Charles et al., 2007).

John Kasarda has developed a theory in which he uses to describe the correlation

between internet activity and travel. Telecommunication has provided the opportunity for

people to communicate with far-off contacts with whom we would not have otherwise

been in contact. This connection serves to peak our curiosity and increases the desire

to travel those great distances. For every message that is sent, – whether it is voice or

text based – there is a greater chance it will lead to a face-to-face meeting. “Facebook

friends drop in and become real ones; stray tweets on Twitter breed followers, contacts,

and business trips. The more wired we are the more we fly” (Kasarda & Lindsay, 2011,

p. 113).

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Empirical evidence supporting this fact can be found in the 83% increase in air

travel during the internet years. Researchers claim that this is not a “coincidence but a

correlation because technology is only a starting point for long distance relationships; it

actually makes us more inclined to fly” (Kasarda & Lindsay, 2011, p. 113). Time

magazine once estimated that jet powered air-travel had shrunk the world by 40%.

Kasarda furthers the reference saying that the world is flat, making most locations easily

accessible (Kasarda & Lindsay, 2011).

In the United States, business-related travel accounts for $246 billion in spending

and 2.3 million American jobs. Nearly half of the spending and half of the jobs can be

directly linked to business meetings and events. “For every dollar invested in business

travel, businesses experience an average $12.50 in increased revenue and $3.80 in

new profits. A 10% increase in business travel spending would increase multi-factor

productivity, leading to a U.S. GDP increase between 1.5% and 2.8%” (U.S. Travel

Association, 2011). “The wealthier we become, the more we value our time, and the

more we value our time, the more likely we are to fly” (Kasarda & Lindsay, 2011, p. 99).

Simply put, time equals money.

In a given year, as many as 88 million passengers stream through an airport

terminal. Comparatively speaking, only eight to 12 million people peruse though a large

mall on an annual basis. When you consider that airline passengers have significantly

higher incomes than the average person (three to five times higher than national

average) it makes sense that airports now have other commercial attractions besides

coffee shops and magazine stands. For example, McCarran international Airport in Las

Vegas has a museum and Arlanda Airport in Stockholm has a chapel that served as the

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location for 500 weddings in 2007 (Kasarda, 2008, p. 51). The fact that airline

passengers are captive audiences in airports also expectedly has an impact the

increasing presence of commercial attractions.

Development around the airport reflects the needs of the airport passenger as well

as the airport employee. An example of this is childcare services for airport employees

(Kasarda, 2008). With all of attractions in airports, people do not want to leave the

airport during a trip. This leads to the creation of what Kasarda terms as ‘airworld’

(Kasarda & Lindsay, 2011). Landside airport development is also occurring. Airports are

incorporating a greater diversification of shopping and leisure venues (i.e., conference

and exhibition centers; logistics and free trade zones; and facilities for processing time-

sensitive goods) (Kasarda, 2008). Researchers argue that it was an easy choice for

airports to take advantage of commercial expansion and “reinvent themselves as slick

conference centers and convention sites” (Kasarda & Lindsay, 2011, p. 107).

Whether by partnering with third-party real-estate development firms or by doing it

in-house, real-estate development has become a way for airports to develop and

manage landside property. Even though airports have designated boundaries, many

have development occurring ‘outside the fence’. This can be analogously compared to

urban development and how development does not cease at political boundaries. In

some cases, airports are acquiring and operating other airports through special

investment management provisions (Kasarda, 2008). The acquisition of excess land

around airports creates a physical buffer to airport operations and also may allow for

future expansions. These land management practices also allow for the mitigation of the

negative externalities associated with abutting non-compatible land uses.

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The aerotropolis concept is based on the economic principle of agglomeration

economies (Charles et al., 2007, p. 1013). Arthur O’ Sullivan (2009) describes

agglomeration as the tendency for firms to locate close to one another. Complementary

and sometimes competing firms may cluster to share intermediate inputs and labor

pools; the result of which lead to increased productivity and economies of scale.

In fact, Kasarda (2008) claims that airports are “more expansive and important for

employment growth, business competitiveness and urban form than prior transit center-

oriented developments” (p. 50).

Benefits of the Airport in the Community

As Kasarda indicates, the presence of airports in a community is beneficial for the

local area. When talking about the economic prosperity of an airport and the local area,

concurrently, the ‘chicken and egg’ principle often applies. Airports create beneficial

results for the overall economy and the overall economic prosperity benefits the further

growth and helps ensure the continued success of an airport. Kasarda and Lindsay

(2011) claim that the efficacy of airports and air travel is a direct indicator of the health

and prosperity of the economy. There is a direct correlation between the health of the

airline industry and overall economic health. This concept can be eloquently

summarized in a few words; “air travel follows the money” (Kasarda & Lindsay, 2011, p.

98). The airline industry – the more specific surrogate of the aviation industry – also

generally abides by the aforementioned principle. (Vasigh et al., 2008, p. 20). Since the

deregulation of the airline industry in 1978, the national growth domestic product (GDP)

has grown at an average rate of 2.6% while the large commercial airline carriers have

grown at an average of 4.8%, in terms of revenue. Gross domestic product is “the total

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market value of all final goods and services produced in a country in a given year”

(Vasigh et al., 2008, p. 19).

Not only can airports be used as a measure of overall economic prosperity, they

are seen by policy makers as “strategic assets to the regional and national economy”

(Hakfoort et al., 2001, p. 596). Recent conceptualization has brought about the thinking

that airports not only serve as a transportation hub but also as a ‘growth pole’ to spur

regional economic activity. The presence of airports in the region creates two way

interactions with the local economy (Hakfoort et al., 2001).

Airports are capable of producing large tax revenues for municipalities. They can

also be attributed with supporting employment opportunities in a region. A growing

number of airports employ upwards of 50,000 daily workers. Using the U.S. Census

definition, that makes those airports metropolitan central cities (Kasarda, 2008). In the

case of O’Hare International Airport in Chicago, proposed additions and renovations to

the airport is projected to create 185,000 service jobs in the region (McMillen, 2004).

“Airports are spawning aviation-linked clusters of hotels; convention, trade and

exhibition facilities; corporate offices; and retail complexes along with culture

entertainment and recreation centers” (Kasarda, 2008, p. 50). In Las Vegas, when the

megaresorts opened 20 years ago, the number of patrons doubled in proportional

relation with air passengers to the area. Today, Las Vegas is the economic benefactor

of to nearly 50 of the nation’s largest tradeshows (Kasarda & Lindsay, 2011). “Major

airports serve as regional, multi-modal surface-transportation nodes and as magnets for

business locations, commercial transactions, information exchanges and leisure

activities.” (Kasarda, 2008, p. 50).

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Air traffic is projected to see continued growth for the foreseeable future. (Hakfoort

et al., 2001, p. 596). In 2006, the International Civil Aviation Organization estimated that

the aviation industry (and its effects on supporting industries that provide aviation

specific inputs or consumer products) was responsible for as much as 4.5% of the

global GDP. The total economic contribution of air transport can be measured by

looking at the employment and income effects derived from its direct economic activities

on the one hand, and from its indirect and induced activities (multiplier effect) on the

other hand. Studies show that every “$100 of output produced and every 100 jobs

created by air transport trigger additional demand of US $325 and in turn 610 jobs in

other industries” (Flores-Fillol & Nicolini, 2006, p. 3-4). Air cargo is also a sector of the

air industry that is expected to grow in the coming future. Aerospace industry leaders,

Boeing and Airbus, predict an annual 6% growth in global air cargo for the next two

decades (Vasigh et al., 2008). Global population growth plays an important role in the

predicted growth of air traffic. This is especially the case in developing countries like

India and China which has experience a sharp upturn in air travel. It is important to note,

however, that this principle is most applicable when population growth is accompanied

with income growth (Vasigh et al., 2008, p. 19). Simply put, air travel is the fastest

growing mode of transportation in the United States, within the context of intercity travel

(Başar & Bhat, 2004, p. 889). One can only assume that growth of the aviation industry

will continue to provide beneficial outcomes for the rest of the economy.

The opposite economic relationship between airports and the overall economy (as

mentioned earlier) can also be exemplified. Economic growth and prosperity leads to

greater employment and economic activity. This leads to increased business related

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travel. Business travel is the most important segment of patronage for the airline

carriers. The authors of the book Introduction to Air Transport Economics claim that

international financial centers like London and New York experiences a large amount of

air traffic growth. Increased air cargo traffic can also be attributed to overall economic

growth. An additional point is that when household income increases during periods of

economic activity, more discretionary income is available for families to use for leisurely

trips (Vasigh et al., 2008, p. 19). In both cases, it can be stated that the demand for air

travel increases with economic growth. Conversely, the prosperity of airports can lead to

further economic growth for the locality. Thus, an economically reinforcing relationship

exists between airports and the overall economy.

Economic Principles of Air Transportation

The impacts of airport development and operations can be explained via the use

of economic principles. Economic impact is a summation of total impact and is divided

into three types: direct, indirect and induced impacts. The easiest way to describe direct

impact represents economic activities that would not have occurred with the absence of

air transportation. These impacts are also referred to as first-tier economic activities. In

the air transportation industry, both airlines and airports provide the economy and local

communities with a direct economic impact. The employment that is specific to airport

operations is an example of direct impact employment. This includes fixed-based

operators and other airport personnel (Vasigh et al., 2008).

Indirect impacts are second-tier economic impacts that usually occur off-site.

These activities are directly propagated or supported because of air transportation

activities. Some examples of indirect economic impacts include services provided by

travel agencies, hotels, rental car companies, restaurants, and retail establishments.

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These industry sectors are the ones that are most apparent near airports because of the

central place theory. They have a strong relationship to the aviation industry and their

services or goods are supported by airport activities. Typically, indirect economic

impacts are generated by visitors that arrive or depart via air transportation (Vasigh et

al., 2008).

For the direct and indirect economic activities to occur, people must be hired by

the different firms. The induced economic impact measures this activity. These impacts

are the multiplier effects that are associated with the employment and income supported

by the direct and indirect economic impacts. So this includes impacts generated from

living expenses of employees at the airport, hotel, retail establishments and restaurants.

Established multiplier effect coefficients determine the effect based on the reiteration of

these economic activities back into the local economy. To entire economic impacts of

the local economic activities are described as the total economic impact. The total

economic impact is the summation of the direct, indirect, and induced impacts (Vasigh

et al., 2008).

Summary

Thanks to John Kasarda and other airport proponents, airports are no longer

simple transportation hubs but instead are regarded as local economic drivers. Many

different industries rely on aviation activity; whether in the form of air cargo or

passenger transportation. The proliferation of internet commerce has created the JIT

logistics model that relies on air freight services to transport goods to the buyer.

Concurrently, the air passenger has propelled the industry forward as business travel

represents nearly half of all air travel.

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The presence of an airport in a community is an economic asset because airports

offer a specialized service that usually draws users into the community. Airports also

make communities more accessible, which further increases the potential for economic

impacts. Therefore, the indirect and induced economic impacts of airports are receiving

increased focus as they represent a large percentage of the economic impacts when

supporting industries agglomerate around airports.

30

CHAPTER 3 DESCRIPTION OF STUDY AREA

The purpose of this chapter is to describe the study area so that the reader may

gain an understanding of the pertinent facts that affect the research.

Orange County Economic Profile

The study area for this research project is Orange County in central Florida.

Though other focus areas are discussed and analyzed in this report, Orange County is

the primary and consistent point of reference throughout the document. Orange County

is bordered by Osceola County (to the south), Lake County (to the west), Seminole

County (to the north) and Brevard County (to the east) (Figure 3-1).

Demographics

The total population of the county was 1,145,956 in 2010, making it the fifth most

populated county in the state of Florida and accounting for 6.1% of the population. The

population is disaggregated into 421,847 households with average size of 2.64 persons.

Nearly a half-million housing units in 2010 were located in the county approximately

13.5% of which were vacant compared to 17.5% in the state and 11.4% nationwide

(U.S. Census Bureau, 2010a).

In 2010, the median household income was $45,140 in Orange County compared

to higher state and national values of $53,093 and $50,046, respectively. In 2010, the

Census Bureau estimated that 12.3% of Orange County families had an income that

was below the poverty level sometime in the 12 prior months. During the same time,

12% of the families had income levels below the poverty level in the state and 11.3% of

fit the same description in the United States. More than 600,000 people in Orange

County were in the labor force in 2010 and 12.8% were

31

Figure 3-1. Map of Orange County Study Area

32

unemployed. This is better than the state unemployment figure of 13.3% but worse than

the national rate of 10.8% (U.S. Census Bureau, 2010c). Thirty percent of the Orange

County residents had earned a bachelor’s degree or higher, as of 2010. Compared to

the state (25.8%) and nation (28.2%), Orange County has a well educated population

(U.S. Census Bureau, 2010b).

The unemployment and vacant property rates show that Florida has been hit

especially hard in the recent economic downturn, compared to the nation. Orange

County does seem to be faring better than the state but unemployment and vacancy

rates are higher than national averages. Despite this higher level of education, median

income in Orange County was below the state and national averages. This may be

because of the large presence of service and tourism related employers who typically

pay less than other industries (Table 3-1). Similarly, a higher percentage of Orange

County families earned wages that were below the poverty level. These are indicators

that Florida and Orange County could benefit from economic development strategies.

Business Establishments

In 2010, the five largest industry sectors (ranked by employment) in Orange

County were as follows: accommodation and food services; retail trade; healthcare and

social assistance; arts, entertainment, and recreation; and administrative and waste

services (Table 3-1). Each industry sector employed more than 50,000 with the highest

employment coming from the accommodation and food services sector – 94,157 jobs in

2010.

Some of the largest private employers include: Walt Disney World, Adventist

Health Systems; Universal Orlando; Orlando Health; Busch Entertainment Corporation;

Lockheed Martin; and Darden Restaurants (Enterprise Florida, Inc., 2012). Darden

33

Restaurants – headquartered in Orlando – is Orange County’s sole Fortune 500

company with reported revenue of $7.4 million in 2010 (Cable News Network, 2012).

Table 3-1. Top 5 Orange County Industry Sectors, by Employment

Industry Employment Percent of Total Employment

NAICS 72 Accommodation and food services 94,157 16.3%

NAICS 44-45 Retail trade 67,900 11.7%

NAICS 62 Health care and social assistance 62,944 10.9%

NAICS 71 Arts, entertainment, and recreation 57,147 9.9%

NAICS 56 Administrative and waste services 56,955 9.8%

Transportation Assets

More than a dozen state and federal highways provide the backbone of the

surface-based transportation infrastructure in Orange County (Figure 3-2). Federal

Interstate 4 is a primarily east-west corridor that traverses the entire county. Two other

federal highways – US-441 and US-17/92 – also pass through the county. Ten state

highways crisscross the county and provide increased transportation mobility. Surface

transportation is complimented by three railroad operators that transport people and

goods through the county – Amtrak, CSX, and Florida Central (Enterprise Florida, Inc.,

2012).

Twenty-nine airports (including heliports and seaplane bases) are located within

the jurisdictional boundaries of Orange County. This count includes both public and

private-use airports. The four public-use airports are Orlando International Airport,

Orlando Executive Airport, Orlando Apopka Airport, and Bob White Field. It is important

to make special note of Orlando International Airport as it is one of the busiest airports

in the country (ranked by enplanements). In 2010, Orlando International Airport ranked

thirteenth in the nation and second in the state, by number of enplanements. Only

Miami International Airport had more enplanements, by a slim margin, in 2010 than

34

Orlando International Airport (FAA, 2011). Orlando Apopka Airport and Bob White Field

will be discussed in greater detail later in this chapter, as they are the focus of this

research.

State Road 429 Extension Corridor

Orange County is the primary study area boundary because of the availability of

the data used in this research. The following collection of Zip codes – henceforth

referred to as the State Road (SR) 429 Extension Corridor – represents a more specific

area within Orange County for which the developmental impact are assessed. The SR

429 Extension Corridor includes three major areas of development. The Wekiva

Parkway Interchange Area is a mixed-use development planned for an area bordering

the north end of Apopka’s city limits. The second area is a regional airport and aviation

business park. It is just west of the Apopka city limits and it runs along SR 441. The

third site is the Westside Research Park, located at the south end of Apopka, is an

agricultural-based business park.

The SR 429 Extension Corridor area is composed of 10 Zip codes (Figure 3-3).

The Zip codes are as follows: 32703; 32712; 32757; 32798; 32818; 32830; 34734;

34747; 34761; and 34787. This area was established for use in a different economic

evaluation of the proposed extension of Florida State Road 429. The SR 429 Extension

Corridor area was also used in this project because of the availability of data from the

larger economic assessment.

35

Figure 3-2. Map of Orange County Transportation Infrastructure

36

Figure 3-3. Map of SR 429 Extension Corridor Study Area

37

West Orange Airport Authority

The West Orange Airport Authority (WOAA) is a tri-city committee whose goal is

to enhance the aviation accessibility in west Orange County. In 1999, the WOAA

become an independent special district by Florida legislative order. In 2007, another

legislative order assigned jurisdictional boundaries to this district based on the

recommendations of a private feasibility assessment. This area encompasses an area

in west Orange County, north of Lake Apopka and west of US-441 (Figure 3-3). It

shares similar boundaries with the Central Florida Business and Aviation Center

(Orlando Aviation Consultants, 2011). This area includes three airport facilities –

Orlando Apopka Airport, Bob White Field, and Orlando North Airpark.

The Florida Aviation System Plan (FASP) is a statewide aviation system plan

created in 2005 by the Florida Department of Transportation (FDOT). It combines

traditional planning elements with intermodal and strategic planning elements to plan for

the state’s aviation needs. FASP breaks up Florida into nine regions of differing size.

Orange County and WOAA are both completely within the East Central Metropolitan

Area region (FDOT, 2012).

Orlando Apopka Airport Profile

The Orlando Apopka Airport is a privately owned, public-use general aviation

(private and non-scheduled commercial flights) facility. It is located about 17 miles

northwest of the city of Orlando, near the city of Apopka (Figure 3-3) (FDOT, 2010b).

The airport operates with a single 3,987 foot long asphalt runway. Due to infrastructure

limitations, the airport facilities are only capable of handling smaller aircraft (FDOT,

2010d). In 2008, Orlando Apopka Airport was home to nearly 22,000 general aviation

flights, accounting for 1% of general aviation operations in the East Central Metropolitan

38

Area region of FASP. Airport officials report that nearly 35% of airport activity is related

to flight training and an estimated 50% of operations are business related. Tourism-

related activity comprises the nearly 15% of remaining airport activity (FDOT, 2009;

FDOT, 2010b; FDOT, 2010d).

The airport is located less than two miles from a 10-acre industrial park and is

thought to support the transportation needs of the site. Though no FAA or FDOT

approved master plan is required for this facility, airport owners have continually

attempted to update the existing facilities. Recent modifications include a recently

lengthened runway and a newly constructed terminal building. A major barrier to further

expansion is the airport’s proximity to environmentally sensitive land just west of the

property. Despite the barriers of physical growth, owners expect more individuals and

corporations will operate out of Orlando Apopka Airport in the coming future as many try

to avoid the traffic at the larger airports in the region (FDOT, 2010b).

A 2010 study classified Florida’s airports into a categories based on general

aviation visitor spending. Orlando Apopka Airport is in a class that includes 21 other

airports. These airports averaged 3.1 persons per aircraft operation and had an average

of $110 of visitor expenditures per trip. The airport supports more than 230 workers who

earn more than $7.5 million annually. This employment represents more than airport

employment; it represents the employment of the airport tenants, construction workers,

and any other jobs supported by airport activity. The airport’s annual direct expenditures

are just shy of $10 million and that results in more than $18 million in total annual

economic output. The total output is measured by counting employment, annual payroll,

and annual economic activity (Wilbur Smith Associates, Inc., 2010; FDOT, 2010d).

39

Bob White Field Profile

Like the Orlando Apopka Airport, Bob White Field is a privately owned, public-use

general aviation airport. It is located about four miles northwest of Orlando Apopka

Airport, about one mile west of the community of Zellwood (Figure 3-3). The airfield is

equipped with a 3,300 foot grass runway and is served by a 240 square foot terminal

building. Due to infrastructure limitations, the airport facilities are only capable of

handling small aircraft. In 2008, Bob White Field was home to nearly 20,000 general

aviation flights, accounting for less than 1% of regional general aviation operations. The

airport is primarily used for sport aviation and recreational purposes. Little to no flight

operations serve corporate or business users and the airport owners do not envision

much overall growth in the foreseeable future (FDOT, 2010a).

Bob White Field is in a visitor spending tier included 22 other airports. These

airports averaged 2.2 persons per flight and $70 of visitor expenditures per trip. The

airport supports 18 workers that earn a combined total of $580,000, annually. The

airport’s annual direct expenditures ring it at $360,000 with a total economic output of

$860,000 (Wilbur Smith Associates, Inc., 2010; FDOT, 2010c).

Orlando North Airpark Profile

Orlando North Airpark is a privately owned, private-use airport. It is located about

one mile southwest of Bob White Field, straddling the border between Orange and Lake

Counties (Figure 3-3). It operates with a 4,000 foot runway that is aligned in an east-

west direction. The eastern portion of the runway that is in Orange County is 2,860 feet

long and is paved. The remaining 1,140 feet resides in Lake County and is grass

(Orlando Aviation Consultants, 2011).

40

The owner of the airport reported that the airport had 10,000 general aviation

operations in 2008 (Orlando Aviation Consultants, 2011). Since this airport is for only for

private use this facility is not accepted as part of the FASP. This means that economic

and general aviation operation figures are not calculated into regional totals.

Proposed Airport Development

The Central Florida Business and Aviation Center will feature a multimodal

business hub comprised of air, road, and rail assets. The goal is to create a new public

use airport that will support the growing demand for general aviation in the area. The

West Orange Airport Authority hopes that this development will attract businesses and

spur economic growth in the area. To qualify for state and federal funds, the new airport

would need to meet specific criteria to be accepted into the FASP. At that point, it would

be eligible for admittance into the National Plan of Integrated Airport Systems. With

existing railroad tracks and spurs bordering the northern and eastern portions of the

Central Florida Business and Aviation Center boundary, WOAA has plans for

commercial and industrial industry to take advantage of rail accessibility (Orlando

Aviation Consultants, 2011). Essentially, WOAA wishes to turn this area into a small-

scale industrial aerotropolis.

The purpose of the airport master planning process is to establish specific airport

layout, design and jurisdictional judgments. In the meantime, WOAA and the Orlando

Aviation Consultants (2011) have generated a few different development scenarios for

the purposes of estimating costs for the 20-year outlook of the airport. Orlando Apopka

Airport, Bob White Field, and Orlando North Airpark are being considered as possible

expansion points for the new WOAA airport.

41

Conceptual plans

Three main conceptual plans are being discussed for implementation. Each plan

adds additional runway infrastructure to an existing airport or creates new facilities

entirely. There is no indication that any of the proposed conceptual plans have been

identified as more likely to be implemented than any other.

The first concept plan focuses on redevelopment of Orlando Apopka Airport. The

existing 3,987 foot runway would be lengthened in the southward to a total length of

6,000 feet. An additional 6,500 foot asphalt runway would also be constructed in the

north-south direction, adjacent to the existing runway (Orlando Aviation Consultants,

2011). The 6,000+ foot runways would allow the airport to better handle increased traffic

from small business jets (FAA, 2005).

The additional runway would require substantial geotechnical engineering to

create a level grade. The proposed location of that runway abuts a steep slope that

approaches land owned by the St. Johns River Water Management District (Orlando

Aviation Consultants, 2011). Two other runway configurations are also discussed for

this plan. One includes the new runway to run perpendicular to the existing runway. The

second places the new runway in an east-west orientation, north of the existing runway.

The east-west orientation is advantageous because it maximizes wind-based landing

opportunities (City of Apopka, 2012).

A number of other developments are planned in the business aviation center in

conjunction with the airport. An aviation museum is planned for land adjacent to SR

441, near the Orlando Apopka Airport. A commuter rail station, with accompanying park

and ride lot, would be built on the southeast corner of Hermit Smith Road and SR 441.

A commercial center is also planned for land near the rail station. Officials hope that its

42

proximity to the rail station and office developments will help its successful. A trade

school with business incubator is also planned for the area near Hermit Smith Road and

SR 441. Industrial and warehouse distribution developments would be located around

the existing Orlando North Airpark and Bob White Field. Both Orlando North Airpark and

Bob White Field will continue to operate in this case. Rail spurs and improved internal

roadways would increase local and interregional freight mobility (Orlando Aviation

Consultants, 2011).

The second conceptual plan focuses the airport development on the current site

of the Orlando North Airpark. The existing runway would be paved and lengthened by

1,000 feet west, across county lines into Lake County. A new, 6,500 foot asphalt runway

would also be built parallel to the existing runway. No land grading is required for these

runways; however, nearly the entire proposed airport development would be within land

currently owned by the St. Johns River Water Management District (Orlando Aviation

Consultants, 2011).

The second conceptual plan also calls for the same industrial and business

developments as the first concept plan but some would be in different locations. The rail

station and trade school would be moved to a location along SR 441, north of the

proposed site of the aviation museum (Orlando Aviation Consultants, 2011).

The third conceptual plan focuses the airport development on land adjacent to

the existing Bob White Field facilities. The existing grass runway could not be used as a

point of expansion for the airport development. It is too near an active rail line and

residential properties. Two new asphalt runways (the longest being 6,500 feet) would be

built on lands just to the west of the existing airpark. This airport configuration does not

43

require a notable amount of land grading or encroach on land owned by the St. Johns

Water River Management District. This plan also includes the industrial and business

amenities with proposed locations similar to the second model (Orlando Aviation

Consultants, 2011).

Estimated expenditure outlook

Orlando Aviation Consultants (2011) and WOAA have developed cost and

revenue budgets for the proposed airport growth. These budgets were developed to

include flexibility to account for slightly different costs that are attributed to each of the

conceptual plans. The first budget describes detailed construction cost and the other

describes the estimated operational cost and revenues with a 20 year outlook

(Appendix A). The current plan is the FAA, FDOT and local authorities to combine to

sponsor the airport development.

The construction cost budget describes the amount that will be spent in each of

the five phases of the development project. It also specifies how much each agency is

expected the commit to each budget item. The total project cost is just shy of $60

million1 with about $50.8 million coming from the FAA, $4.2 million coming from the

FDOT and the remaining $4.6 million coming from local funds. All of these costs are

projected in 2010 dollars (Orlando Aviation Consultants, 2011). These costs are

universal estimates for all of the concept plans that do not vary despite the different

construction tasks required for each plan.

The 20-year operational budget includes estimated cost and revenue details for

every year from 2010 to 2030. In 2015, the net operating income is expected to drop to

1 Projected construction costs total $59,631,044 but nearly $10,000,000 is unaccounted for in the line

item budget. This disparity appears to be missing in Phase 2 of the project.

44

its lowest point of nearly $-132,000 but economic stability is expected to be established

soon after (Appendix A). The airport is projected to have a net operating income of

$437,000 in 2020 and finish and jump to net operating incomes of $1.1 million and

nearly $1.6 million in 2025 and 2030, respectively. These figures were projected based

on assumptions that include the airport’s operational capabilities and facility use for

each year. An example of the assumptions includes recurring utility, administrative, and

payroll costs (Orlando Aviation Consultants, 2011).

45

CHAPTER 4 ECONOMIC BASE ANALYSIS METHODOLOGY AND RESULTS

This is the first of three chapters used to describe the methodologies and results

employed to answer the research questions in Chapter 1. The purpose of this chapter is

to analyze the public investment in airport development in Orange County. To do this,

an economic base analysis is conducted. Economic base analysis includes the location

quotient technique (LQ), shift-share analysis, and the Esteban-Marquillas extension.

North American Industry Classification System Overview

All industry activities in the United States are classified and described using the

North American Industry Classification System (NAICS). The NAICS industry

designation system is the standard by which the Federal government analyzes the

business economy (U.S. Census Bureau, 2011b). The 2007 version of the NAICS was

used in this study as it was the most recent version of the system available at the time

of the analysis. The Bureau of Labor Statistics (BLS), a subsidiary of the U.S.

Department of Labor, provides employment data classified into NAICS codes via a

website query. Nested, numerical values are used to describe the specific industries; so

as more digits are added, the more specific the industry (Blanco, 2010a, slide 27). Four-

digit NAICS code data was used in because it provided the necessary level of industry

specificity for this analysis. Employment data from 2010 was used because this was the

most recent data available from the BLS at the time the data was collected for the

research. For the purposes of this study, the 2005 and 2010 employment data was used

to calculate LQ, shift-share, and Esteban-Marquillas extension.

Two components of the aviation industry were examined in these analyses. The

primary focus was the NAICS 4881 ‘Support Activities for Air Transportation’ industry

46

sector. This industry sector includes economic activity associated with airport operation,

servicing, repairing, maintain and storing aircraft; all things that will be of normal, daily

activity at the WOAA airport (U.S. Census Bureau, 2011a). This is primary focus of the

research because this industry will have a sustained benefit from the state and federal

investment described in Chapter 3.

The secondary focus was the NAICS 4821 ’Nonscheduled Air Transportation’

industry sector. As the name would indicate, this sector represents economic activity

associated with aerial transportation operating on nonscheduled flights. Nonscheduled

flights include passenger and cargo movement but these flights are chartered instead of

based on a set schedule. These also include recreation and personal use flights. This is

difference than the similar sector NAICS 48111 ‘Scheduled Air Transportation’ which

represents aerial transportation that occurs via scheduled flights. Scheduled flights

generally represent commercial airline (both passenger and cargo) flights. A primary

different is that scheduled flights are flown even if maximum capacity of the aircraft is

not reached (U.S. Census Bureau, 2011a). Since the WOAA airport is not being

designed for or projected to accommodate commercial flights, this researcher deemed it

was necessary to specifically focus on nonscheduled flights as a disaggregated form

from all air transportation activity.

Though the ‘Nonscheduled Air Transportation’ sector is not receiving direct

investment, it was analyzed because the researcher hypothesizes that this sector will be

most affected by secondary spending – indirect impacts – of the investment in airport

operations. Analyzing this industry sector, concurrently, may give further justification for

47

investment in airport operations if it can be proven that there will be substantial

multiplier effects.

Construction activities, though it plays a large role in the eventual economic

impact of airport development, it is not analyzed in this chapter. This chapter focuses on

the justification for public investment; construction activity is simply the means by which

the goal is achieved and is not heavily considered as a reason to validate the

investment. Its impact, however, will be discussed in later chapters.

Employment Dynamics

Before the analyses were conducted, 2005 and 2010 employment data for the

United States, state of Florida and Orange County were examined (Table 4-1).

Employment values for the total base economy, the ‘Nonscheduled Air Transportation’

and ‘Support Activities for Air Transportation’ are provided in the table.

More than 4.4 million jobs were lost in the United States between 2005 and 2010.

Greater than 650,000 jobs and 16,000 jobs were lost in Florida and Orange County,

respectively, during the same time period. The ‘Nonscheduled Air Transportation’ sector

experienced job loss at the national and local level but had an increase of 311 jobs in

the state industry during the same time. During the tough economic times from 2005 to

2010, the ‘Support Activities for Air Transportation’ sector fared well, experiencing an

employment growth in the nation, state, and county. The United States had an increase

of 6,367 jobs while the state added 1,536 jobs. That means that Florida’s industry

growth represents a 24% of the national job growth in the industry. A local employment

increase of 630 represents 41% of the state increase and nearly 10% of the national

increase.

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There is an intriguing trend that begs the question, why did the ‘Support Activities

for Air Transportation’ experienced such substantial job growth while the base local,

state, and national economies were in decline? The following sections of this chapter

set out to understand this trend using the results of the economic base analysis tools.

Table 4-1. 2005-2010 Employment

Industry 2005 US Total

2010 US Total

2005 Florida Total

2010 Florida Total

2005 Orange County Total

2010 Orange County Total

Base Industry Total

110,611,016 106,201,232 6,694,864 6,044,806 594,562 578,477

NAICS 4812 Nonscheduled Air Transportation

44,513 40,790 3,350 3,661 378 294

NAICS 4881 Support Activities for Air Transportation

148,201 154,568 14,869 16,405 1,229 1,859

Source: U.S. Bureau of Labor Statistics, 2012

Location Quotient Analysis

Analysis Overview

The location quotient technique is used to “identify the concentration of an industry

sector in a local economy relative to a larger reference economy” (Blakely & Leigh,

2010, p. 167). In other words, the location quotient technique compares a specific

industry to the entire economy of specific area. In this case, the location quotient was

used to compare the industries of Orange County to both economies of the state of

Florida and United States in 2010. Therefore, Orange County is henceforth referred to

as the ‘local’ economy while the economies of both Florida and the United States are

referred to as ‘base’ or ‘reference’ economies. It is important to note that this technique

only provides a static assessment of the economy; it does not depict whether an

49

industry is growing or declining (Blakely & Leigh, 2010, p. 167). Its primary purpose is to

measure the relative importance of the different industry sectors in Orange County.

The formula used to calculate the location quotient is as follows:

(

) (

)

where

(Blakely & Leigh, 2010, p. 167-168). The U.S. Bureau of Labor Statistics calculates LQs

for different areas throughout the United States. A website interface is used to select

data year, study area selected industry. The results can be outputted in tabular form

from the website. This method was used to calculate location quotient values.

When looking at the results of the location quotient analysis technique, a number

of conclusions can be made. If the location quotient value is less than one, it means that

the local industry holds a smaller concentration of the economy relative to the same

industry of the larger, reference economy. It suggests that the local economy does not

produce enough products or services to meet its need. In this case, the local economy

must import products or services to fulfill the need – referred to as an import economy. If

the location quotient value is equal to one, then the local industry is just meeting the

need for products in the industry and is an indicator that the industry in both the locality

and larger economy hold the same percentage of the employment sector. If the location

quotient value is greater than one, then it indicates that there is a greater proportion of

employment in the local industry when compared to the same industry of the reference

economy. It may also suggest that there is an excess of products and services

50

produced in the locality that can be exported – referred to as an export economy

(Blakely & Leigh, 2010). The possible conclusions are summarized and described in

Table 4-2.

Table 4-2. Location Quotient Values and Corresponding Conclusions

LQ Value Conclusion

LQ = 1 The region has the same percentage of employment in that industry as the larger reference area

LQ < 1 The region has a less than proportionate share of employment in that particular industry

LQ > 1 The region has a greater that proportionate concentration of employment in that particular industry

LQ < 0.75 Suggests opportunities exist for import substitution strategies

LQ > 1.25 Suggests export base industries whose further growth will stimulate the overall economy

Source: Blanco, 2010a; Blakely & Leigh, 2010, p. 167 Analysis Results

Table 4-3 lists the industries and corresponding LQ values for the aviation

industry sectors. The ‘Nonscheduled Air Transportation’ industry has LQ values of 0.84

and 1.32 when compared to the state and nation, respectively. These results indicate

that the county did not meet its need for the service provided by this industry when

compared to the rest of the state. However, when compared to the national economy,

the locality did meet its need for the service. In fact such an excess is produced, that it

served as an export base industry. This LQ value disparity is an indication that the state

had a large proportion of employment in this industry when compared to the entire

nation. While the same can be said about the county, when compared to the robust

industry in the state, the local industry looks average at best.

When looking at the more specific ‘Support Activities for Air Transportation’

industry, the LQ values were 1.18 and 2.21 when compared to the state and nation,

51

respectively. The national LQ value indicates that airport operations had a very high

proportionate concentration of employment than the nation. As such, it represented an

export base economy because of its excess employment. The lower 1.18 LQ value

indicates a higher than proportional employment level in the locality when compared to

the state. However, it did not quite meet the minimum requirements to be considered an

export base industry.

Table 4-3. Location Quotient Results

Industry Orange County to Florida

Orange County to United States

NAICS 4812 Nonscheduled Air Transportation 0.84 1.32

NAICS 4881 Support Activities for Air Transportation 1.18 2.21

Shift-Share Analysis

Analysis Overview

The shift-share analysis is a “powerful technique for analyzing changes in the

structure of the local economy in reference to the state or nation” (Blakely & Leigh,

2010, p. 181). Unlike location quotient, shift-share is a dynamic economic analytical tool

that assesses the changes in the local economy using employment data from two or

more points in time. The benefit to using dynamic analyses is that they provide a better

understanding of what is changing in the economy and helps analyst plan for

anticipated job growth (Blakely & Leigh, 2010). Economic data from 2005 was used as

the starting point and data from 2010 was used at the ending point to conduct this

analysis. An advantage of shift-share analysis is that local employment trends are

normalized based on the trends at the state and national levels. Therefore, results will

not be skewed despite overall economic fluctuations during the five year period.

52

Like the location quotient analysis, the shift-share analysis was conducted by

comparing the Orange County economy to the economies of both the state of Florida

and United States. The analysis is separated into three parts – economic growth,

proportional shift, and differential shift. Each provides a hypothetical local job shift value

based on different comparisons. The sum of the total share, mix shift, and competitive

shift equals the actual net job shift for the locality

The economic growth portion – also referred to as total share – of the analysis

puts the direction of the economy into context and illustrates how local industries are

affected as the base economy changes. This portion of the shift-share analysis is used

to compare the growth (or decline) of local industries relative to that of the larger

economy (Blanco, 2010b). This makes it easy to identify how many jobs were created

(or lost) relative to changes in the base economy. A negative economic growth value

indicates that the reference economy, as a whole, was in decline during the specific

time period. A positive number would indicate that the economy as a whole experienced

growth. A value of zero would indicate that the economy experienced a stagnant level of

growth during the time period.

Proportional shift – also referred to as mix shift – can inform the researcher of the

rate of growth (or decline) of a particular industry in relation to all other industries in the

larger economy. It “identifies the industries in the local economy that is contributing to

the growth and decline of the economy” (Blanco, 2010b; Blakely & Leigh, 2010, p. 182).

A proportional shift value of zero indicates that the local industry is proportional to the

overall economy. A negative value indicates that the industry, as a whole, in the

reference economy was in decline relative to the entire reference economy during the

53

specified time. A positive value indicates that the industry, as a whole, in the reference

economy if growing relative to the entirety of the reference economy. The actual mix

shift coefficient indicates the number of jobs gained or lost at the local level because of

dynamism of the industry relative to the entire economy at the base level.

Competitive shift – also referred to as differential shift – compares the health of a

specific industry, on the local scale, to that of the same industry on the national scale

(Blanco, 2010b). This portion of the shift-share analysis that is most often used by

analysts to determine whether local industries are growing or declining relative to the

same industry at the state or national level. When an industry in the reference economy

is growing, competitive shift identifies the local industries that are growing faster than

their national counterparts. Similarly, if an industry in the reference economy is

declining, the competitive shift indicates the local industries that are declining less than

their national counterparts. Both of these situations are ideal and can be identified by a

positive competitive shift value (Blakely & Leigh, 2010).

The formula used to calculate the shift-share is as follows:

[

] [

( )

( ) (

)] [

( )

( ) (

)]

where

Economic Growth Proportional Shift Competitive Shift

54

(Blanco, 2010b). Either economic or employment data can be used to calculate the

shift-share but employment data was used (Blakely & Leigh, 2010). In this study,

Orange County’s industry employment was compared to both the state and national

employment figures.

Analysis Results

Tables 4-4 and 4-5 display the shift-share results for the aviation industry sectors,

when compared to Florida and the United States. In general, positive values are

preferred instead of negative values but positive values do not always indicate a healthy

industry or trend.

Table 4-4. 2005-2010 Shift-Share Results for Orange County to Florida

Industry Total Share

Mix Shift Competitive Shift

Actual Net Job Change


-36.70 71.79 -119.09 -84


-119.33 246.29 503.04 630

Table 4-5. 2005-2010 Shift-Share Results for Orange County to United States

Industry Total Share

Mix Shift Competitive Shift

Actual Net Job Change


-15.07 -16.55 -52.38 -84


-49.00 101.80 577.20 630

Economic growth

The total share values for the aviation industries are both negative when

compared to the state and nation. The negative values from all of the industry sectors

indicate an overall decline in the reference economies. As was depicted in Table 4-1,

the United States and Florida suffered net job losses during the study period. These

values represent the proportional loss of employment in the local industry, as a function

55

of the decline of the larger economy. For example, if the Orange County economy were

to follow the same downward trend as the overall state economy, the ‘Support Activities

for Air Transportation’ industry sector would have lost 119 jobs. Similarly, the industry

would have suffered 49 job losses if Orange County were to decline as did the United

States economy. The same can be said for the ‘Nonscheduled Air Transportation’

industry sector. This relationship is best described using the analogy of boats on rising

and falling seas. As the water rises, so do the boats and vice versa. The boats – which

represent the local industries – are affected by the ebb and flow of the overall economy;

the local industries are a function of the larger economies.

Mix shift

Each of the aviation industries had a positive mix shift value when the local

industry was compared to the state economy. The positive mix shift values indicate that

the aviation industries at the state level fared better than the overall state economy. An

industry has an advantage when it is growing faster (or declining less) than the

economy as a whole. For example, 246 Orange County ‘Support Activities for Air

Transportation’ industry jobs would be gained if the industry trended as did the industry

in the state economy.

The mix shift values for the two industries when compared to the nation are split;

one is positive and one is negative. The positive mix shift value for the nation is an

indication that the national aviation industries have a proportional advantage to the

entire national economy. Knowing that there was a decrease in employment in the

industry at the national level and the overall state economy (Table 4-1), the positive

value indicates that there was less of an employment decrease in the local industry.

That is, the ‘Support Activities for Air Transportation’ industry in Orange County would

56

have gained 101 jobs if the local industry increased as proportionately as the industry at

the national level. Conversely, the negative mix shift value implies that the air

transportation industry in Orange County was negatively disproportionate to mix of the

industry to the overall economy at the national level. That is, the ‘Nonscheduled Air

Transportation’ industry in Orange County would lose 17 jobs if the local industry was

proportionally affected by the industry shift at the national level.

Competitive shift

Positive competitive shift values indicate that the local industry experienced a

positive proportional shift in relation to the industry of the reference economy. That is,

the industry was growing at a faster rate (or declining at a slower rate) compared to the

same industry at the reference economy level. The competitive shift accounted for a

growth of 503 Orange County jobs in the ‘Support Activities for Air Transportation’

sector, when compared to the state and a growth of 577 jobs when compared to the

nation. Conversely, 119 jobs were lost in the ‘Nonscheduled Air Transportation’ sector

because of the state competitive shift. The industry also would lose 52 jobs because of

the national competitive shift.

Esteban-Marquillas Extension

Analysis Overview

The Esteban-Marquillas extension uses the basis of the shift-share analysis with

two modifications; the redefinition of the competitive shift portion and the addition of the

allocation effect (Blanco, 2010b). The redefined competitive shift acts similarly to the

original competitive shift but is uses a local employment figure that is normalized to a

reference economy benchmark. This new employment value is called the homothetic

employment. Homothetic employment (formula provided below) is a hypothetical

57

employment level calculated based on industry proportionality, at the state or national

level. Therefore, the competitive shift value calculates a hypothetical local industry

employment value based on the normalized employment value – homothetic

employment value. The allocation effect is broken into two parts – the specialization

effect and the comparative advantage; both tell a slightly different bit of information. The

specialization effect informs the researcher if the locality has a specialized industry and

the comparative advantage tells if the locality has a comparative advantage compared

to the reference economy (Blanco, 2010b).

The formulas used for the homothetic employment and entire Esteban-Marquillas

extension are as follows:

(

)

[

] [

( )

( ) (

)]

[(

)

( ) (

)]

( ) [(

) (

)]

where

Economic Growth Proportional Shift Redefined

Competitive Shift

Allocation Effect

58

(Blanco, 2010b). The equations for the specialization effect and comparative advantage

are extracted from the allocation effect and listed as follows:

( ) [(

) (

)]

where

(Blanco, 2010b). If the specialization effect value is greater than zero, the locality is

considered to be specialized. The specialization effect value is less than zero, the

locality is not specialized. If the comparative advantage value is greater than zero, the

locality has a comparative advantage and if the value is less than zero, the locality does

not have a comparative advantage. If the industry is specialized but there is no

competitive advantage, then intervention may be effective. If the industry is not

specialized but there is a comparative advantage, intervention may be effective (Blanco,

2010b).

Analysis Results

Tables 4-6 and 4-7 describe the Esteban Marquillas Extension results when

compared to Florida and the United States, respectively. The state benchmarked

homothetic employment for the ‘Support Activities for Air Transportation’ industry sector

Specialization Effect

Comparative Advantage

59

is larger than the actual employment, which creates a negative specialization effect.

Despite the negative specialization effect, a positive value of 540.49 was established for

the redefined competitive shift. When compared to the nation, the smaller homothetic

employment produces a positive specialization effect. This, again, results in a positive

redefined competitive shift. The positive redefined competitive shift values signify the

amount of jobs created based on industry trends, when the homothetic employment

shift is applied.

Table 4-6. Esteban Marquillas Extension 2005-2010 Orange County to Florida

Industry Homothetic Employment

Redefined Competitive Shift



NAICS 4812 Nonscheduled air transportation

297.51 -93.73 80.49 -0.32

NAICS 4881 Support activities for air transportation

1320.50 540.49 -91.50 0.41

Table 4-7. Esteban Marquillas Extension 2005-2010 Orange County to United States

Industry Homothetic Employment

Redefined Competitive Shift



NAICS 4812 Nonscheduled air transportation

239.27 -33.16 138.73 -0.14

NAICS 4881 Support activities for air transportation

796.62 374.13 432.38 0.47

The ‘Nonscheduled Air Transportation’ industry sector has homothetic

employment values less than the actual industry employment values, when compared to

both the state and nation. When the homothetic employment values (297.51 for the

state and 239.27 for the nation) are subtracted from the actual employment (378), the

two positive specialization effect values are the result. The resulting values indicate that

the ‘Nonscheduled Air Transportation’ industry sector had 80.49 and 138.73 more jobs

in the local industry than was the amount that would be hypothesized based on the

60

structure of the industry in the state and nation, respectively. Both redefined competitive

shift values for the industry are negative. Assuming that the local industry employment

was established based on the benchmark; the values indicate the hypothetical number

of jobs that declined because of the industry trends at the state and national level.

Summary

The results presented in this Chapter are analyzed and discussed in Chapter 7. It

is important to remember that the results of these economic base analyses are not

taken out of context. Though conclusions are made about the health of local industries,

they are only made in reference to state and national employment proportions. These

methodologies rely on the assumption that the national and/or state economies,

themselves, are well proportioned.

61

CHAPTER 5 INPUT-OUTPUT ANALYSIS METHODOLOGY AND RESULTS

This chapter describes the methodology and results of the input-output analysis.

It is the second of three chapters that describes the methodology and results of the

analyses used to answer the research questions. The purpose of this chapter is to

quantify the economic impact of airport development.

Analysis Overview

The input-output analysis was created to measure the economic impact of

monetary transactions between different sectors of the economy in a given year. In

normal economic transactions, firms purchase goods and services from multiple

agencies to produce its goods and/or services. The resulting goods and services are

used by other firms and consumers to conduct their business. The cycle repeats itself in

a healthy economy. This multiplier effect is the basis of economic development analysis

for the input-output technique. Multipliers are represented by coefficient values that

usually range from 1.5 to 1.75. It allows for the examination of linkages between

industry sectors (Blakely & Leigh, 2010; Blanco, 2010c).

The input-output analysis has been used to measure the economic impact of

airports for more than 20 years. Researchers were polled in a 2008 study and the

consensus was that input-output models are the most useful analysis for measuring an

airport’s economic significance (Transportation Research Board, 2008).

Three outputs are produced by this methodology – the direct impacts, indirect

impacts, and induced impacts. As was mentioned in Chapter 2, these three impact

types measure different layers of transactions. Multiplier coefficients, employment

62

impacts, and monetary impacts are produced as results for each transaction level

(Blakely & Leigh, 2010).

IMPLAN Software

For the purposes of this research project, the input-output analysis was conducted

using the computer software package called IMPLAN® Version 3.0. The name IMPLAN

is an acronym that stands for impact analysis for planning. Multiple software packages

can be used to perform this analysis but according to researchers, IMPLAN is one of the

best programs. It is the industry leader and is in widespread use by economic

development professionals (Blakely & Leigh, 2010).

An IMPLAN model is basically a session in which analysis settings (study area

included) are set. Multiple scenarios (referred to as activities) can be created and

analyzed in each model. An activity is described as a group of related spending events

that represents some sort of industry change (MIG, Inc., 2012). To illustrate the

components necessary to create an activity, consider the following example. An activity

may be the development of a new retail store. This activity would be comprised of

multiple events that represent the different economic transactions necessary to develop

the store (i.e., architectural, construction, and advertising services). A sector

designation would be assigned to each event and dollar amount would be entered to

represent the amount that would be spent in each industry. IMPLAN uses its own set

codes for the different industry sectors (MIG, Inc., 2011a). They are not the same as the

NAICS codes but can easily be cross-referenced with a sector search query built into

the software.

Two models were created for this analysis and each of the airport scenarios listed

below was run in each model. The first was focused on the economic impacts for the

63

entirety of Orange County. The SR 429 Extension Corridor was the study area for the

second model, with a slight modification. Two of the 10 ZIP code jurisdictions (32757

and 34747) cross into Lake County and were omitted from the study area of this portion

of the analysis. This is because the IMPLAN dataset only represented Orange County;

data was not available for the two ZIP codes that crossed the county border.

Construction Costs

Several IMPLAN scenarios were created to represent the different scenarios that

were examined for this project. The first was to look at the economic impacts of the five

phases of airport construction. Table A-1 described detailed construction expenses for

each phase of the project. The model was created to take into account, each listed

construction expenditure. NAICS sector codes were attributed to each budget line in the

table, based on the expenditure title. These sector codes were then cross-referenced

with the corresponding IMPLAN sector code. The IMPLAN software fails to include

specific sector codes for the different types of construction events but rather groups

them under one generic sector code. Therefore, the majority of the budget items were

eventually assigned to that generic construction sector code. Lastly, each activity event

was assigned an industry sales value equivalent to and these figures were calculated in

2010 dollars. The five phases of construction were combined and analyzed as a single

scenario.

Operational Costs

Data from the 20-year budget outlook was used for this portion of the analysis. For

this, data from Table A-1 was used. Four separate activities were created, one for each

of the following budget years (2015, 2020, 2025, and 2030). A single event – with a

sector to represent airport operations – was used for each of the activities. When this

64

sector was applied, the IMPLAN software assigned default employment values to the

event; however, employment figures were used in the analysis instead of the assigned

default values. Using case specific employment numbers rather than software defaults

creates more accurate results. The total operating expenses sums from the table was

used in the model as the industry expenditure values. It is important to note that each

activity was run with the appropriate modifiers to simulate costs in the particular years.

For example, the 2015 expenditure totals were entered and the model was run to

simulate impacts in 2015 as opposed to the default setting of 2011.

Analysis Results

The IMPLAN software produced economic impact summary tables for each of the

scenarios. The direct, indirect, and induced effects are summarized for the projected

employment, labor income, value added, and output figures. The employment figures do

not discriminate from full-time or part-time jobs. They are not full-time equivalents so it is

possible for workers to work multiple jobs in the model. The labor income measure is

calculated by adding the total wages of the workers and sole-proprietor incomes. It is

important to note that this figure also includes employee benefits like insurance or

retirement packages and not simply the take home pay. The value added measure is

the sum of the labor income measure, as well as costs like property income and indirect

business taxes. The total output is the total value of economic production. It is the sum

of the value added measure and the cost of making the goods needed to produce the

end product or service (MIG, Inc., 2012).

Multiplier Coefficients

IMPLAN, and all other input-output analysis tools, use multiplier coefficients. The

power of input-output software packages reside with their isolation of local multiplier

65

coefficients. These coefficients are unique to the study area and are established based

on the presence of firms from different industry sectors. At the national level, every firm

in the United States is taken into account and the presence of a greater number and

diversity of firms would create higher multiplier effects. Therefore, regional multipliers

would never supersede national multiplier values because the less diverse industry

presence at the regional level yields a smaller multiplier coefficient.

The industry sectors described in Table 5-1 include ‘Nonscheduled Air

Transportation’, ‘Support Activities for Air Transportation’, and the four sectors directly

affected by the construction investments. Of the sectors in Table 5-1, the

‘Nonscheduled Air Transportation’ sector has the lowest multiplier with a value of 1.32

for the SR 429 Extension Corridor and 1.43 for Orange County. This means that if one

dollar was invested in this sector, there would be $1.32 of total economic impact in the

SR 429 Extension Corridor or $1.43 in the entire Orange County.

Table 5-1. Study Area Multiplier Coefficients

Industry SR 429 Ext. Multiplier

Orange County Multiplier

NAICS 23 Construction 1.40 1.63

NAICS 4812 Nonscheduled Air Transportation 1.32 1.43

NAICS 4881 Support Activities for Air Transportation 1.45 1.70

NAICS 5413 Architectural, Engineering, and Related Services

1.48 1.76

NAICS 5416 Management, Scientific, and Technical Consulting Services

1.49 1.76

NAICS 5629 Remediation and Other Waste Management Services

1.40 1.60

66

Construction Scenarios

IMPLAN uses the study area multipliers and predefined industry linkages to create

impact estimates for a number of performance measurements (i.e., employment, labor

income, total value added, and output) for each industry sector. Tables 5-2 and 5-3

describe summarized economic impact for the five phased construction project for the

study area. Airport construction is expected to support 546 jobs in the SR 429 Corridor

and will earn nearly $30 million dollars. With a direct investment of nearly $50 million,

officials can expect more than $70 million of total economic activity in the SR 429

Extension Corridor. Airport construction is expected to support 652 jobs Orange County

jobs. Total worker compensation will exceed $35 million. A direct investment of almost

$50 million will spur more than $82 million of economic activity in Orange County. The

total effect is greater for Orange County than it is for SR 429 Extension Corridor

because a larger study area allows a greater opportunity for impacts. This is the result

of larger multiplier effects for Orange County when compared to SR 429 Extension

Corridor.

2015 Airport Operations Scenarios

Tables 5-4 and 5-5 describe the economic impact of airport operations in 2015 for

both the SR 429 Extension Corridor and the entire county. The $2.7 million airport

expenditure is expected to support 44 jobs in the SR 429 Extension Corridor and an

additional five jobs in the county. Workers will earn more than $2.2 million in the SR 429

Extension Corridor and nearly than $2.5 million in the county. Officials can expect nearly

$4 million of total economic activity in the SR 429 Extension Corridor and more than

$4.6 million in the entire county.

67

Table 5-2. Construction Scenario Impact Summary for SR 429 Ext. Corridor

Impact Type Employment Labor Income (in 2010 dollars)

Value Added (in 2010 dollars)

Output (in 2010 dollars)

Direct Effect 372.2 $22,362,318 $25,255,235 $49,700,044

Indirect Effect 70.7 $3,409,615 $5,203,177 $8,558,475

Induced Effect 103.4 $4,166,919 $7,683,594 $11,937,569

Total Effect 546.2 $29,938,852 $38,142,006 $70,196,088

Table 5-3. Construction Scenario Impact Summary for Orange County




Direct Effect 386.7 $22,759,733 $25,691,527 $49,700,044

Indirect Effect 122.1 $6,466,133 $9,502,520 $15,550,142

Induced Effect 143.7 $6,128,985 $10,794,631 $17,272,252

Total Effect 652.5 $35,354,851 $45,988,678 $82,522,439

Table 5-4. 2015 Airport Operations Scenario Impact Summary for SR 429 Ext. Corridor




Direct Effect 34 $1,740,095 $1,829,098 $2,721,308

Indirect Effect 2.9 $154,314 $216,488 $366,299

Induced Effect 7.1 $313,867 $579,385 $881,820

Total Effect 44 $2,208,276 $2,624,971 $3,969,427

Table 5-5. 2015 Airport Operations Scenario Impact Summary for Orange County




Direct Effect 34 $1,740,095 $1,826,047 $2,721,308

Indirect Effect 5.8 $295,727 $424,063 $716,954

Induced Effect 9.3 $439,578 $774,846 $1,235,647

Total Effect 49.2 $2,475,399 $3,024,957 $4,673,909


Table 5-6 and 5-7 describe the economic impacts of the proposed 2020 airport

expenditures in the SR 429 Extension Corridor and Orange County. The airport is

expected to support 64 employees in 2020. An additional 22 employees will be

supported in the SR 429 Extension Corridor and more than 35 additional jobs will be

68

supported in the county. The increased employment from 2015 is based on the

assumption that the airport will operate at an increasing level every year through 2030.

The workers in the SR 429 Extension Corridor will earn more than $4.8 million and

nearly $5.6 million in the county. With a direct investment of $8.7 million, total economic

impact will exceed $11.8 million in the SR 429 Extension Corridor and $13.9 million in

the county.


Tables 5-8 and 5-9 describe the economic impact of the 2025 airport operation

scenarios for the SR 429 Extension Corridor and Orange County. In 2025, it is expected

that the airport will directly employ 94 workers. A total of 129 workers will be supported

in the SR 429 Extension Corridor and will earn nearly than $8.2 million. The total

economic impact of airport operations will be nearly than $21.9 million in the SR 429

Extension Corridor. Looking at the entire county, 150 workers will be supported and will

earn about $9.5 million. The total economic impact will be about $25.9 million in the

county in 2025.





Direct Effect 64 $3,660,762 $3,946,511 $8,736,882

Indirect Effect 8.2 $474,295 $665,390 $1,154,856

Induced Effect 14.3 $703,063 $1,299,284 $1,960,038

Total Effect 86.5 $4,838,120 $5,911,185 $11,851,776


Tables 5-10 and 5-11 summarize the economic impacts of 2030 airport operations

in both the SR 429 Extension Corridor and the County. The airport is projected to

employ 124 workers in 2030. Employment totals will reach 175 if just looking at the SR

69

429 Extension Corridor or 206 in the entire county. With a direct investment of about

$28 million, the SR 429 Extension Corridor would experience an economic impact of

about $36.9 million. A $43.9 million impact would be felt in the entire county off of the

same investment.





Direct Effect 64 $3,660,762 $3,924,942 $8,736,882

Indirect Effect 16.2 $908,937 $1,303,389 $2,318,888

Induced Effect 19.5 $1,015,650 $1,791,723 $2,888,631

Total Effect 99.7 $5,585,349 $7,020,055 $13,944,402





Direct Effect 94 $6,124,345 $6,660,881 $16,404,816

Indirect Effect 13.3 $852,565 $1,196,067 $2,138,273

Induced Effect 22.1 $1,196,821 $2,212,599 $3,346,410

Total Effect 129.4 $8,173,730 $10,069,548 $21,889,499





Direct Effect 94 $6,124,345 $6,599,220 $16,404,816

Indirect Effect 26.3 $1,633,854 $2,342,898 $4,411,854

Induced Effect 30.3 $1,741,266 $3,072,607 $5,071,137

Total Effect 150.6 $9,499,465 $12,014,725 $25,887,808





Direct Effect 124 $9,489,795 $10,403,787 $27,945,684

Indirect Effect 19.6 $1,390,385 $1,950,577 $3,605,826

Induced Effect 31.4 $1,881,354 $3,479,291 $5,328,217

Total Effect 175 $12,761,534 $15,833,655 $36,879,727

70





Direct Effect 124 $9,489,795 $10,264,234 $27,945,684

Indirect Effect 38.8 $2,664,531 $3,820,858 $7,655,259

Induced Effect 43.3 $2,751,990 $4,857,256 $8,294,580

Total Effect 206.1 $14,906,316 $18,942,348 $43,895,522

Top 10 Affected Industries

Tables 5-12 and 5-13 describe the top 10 affected industries by the airport

operations investment for each of the analyzed years. The tables display the total output

figures and are ranked by the output results of the 2030 scenario; surprisingly, the

rankings do differ slightly between scenario years.

Not surprisingly, ‘Support Activities for Air Transportation’ represents the highest

output in each of the scenarios because it is the industry that receives the direct funding

investments. A notable industry sector ranked among the top 10 is the ‘Imputed Rental

Activity for Owner-occupied Dwellings.’ It is not a NAICS industry sector but rather one

created by IMPLAN to help describe their results. The sector describes economic

activity associated with owning a home, which include repair and maintenance on the

home. No employment is associated with the industry and the only output by the

industry is home ownership so its further contribution to the economy is naturally limited

(MIG, Inc., 2011b).

Summary

A $50 million investment in construction yields $70.2 million of economic impacts

in the SR 429 Extension Corridor and $82.5 million of economic impacts in Orange

County. A total of 546 and 652 jobs would be supported in the SR 429 Extension

Corridor and Orange County respectively. The 2030 airport operations budget of $28

71

million would yield an economic impact of $37 million in the SR 429 Extension Corridor

and $44 million in Orange County. Airport operations activities would support 175

annual jobs in the SR 429 Extension Corridor and 206 jobs in Orange County. The

results presented in this Chapter are analyzed and discussed in Chapter 7.

Table 5-12. Top 10 Affected Industries for Airport Operations by Output in SR 429 Ext. Corridor

NAICS Sector 2015 2020 2025 2030

4881 Support Activities for Air Transportation

2,438,368.6 6,777,093.6 11,016,365.9 16,246,603.3

Imputed Rental Activity for Owner-occupied Dwellings

142,555.1 291,701.7 450,567.6 642,430.8

531 Real Estate 83,374.7 188,058.3 295,281.0 425,356.4

622 Hospitals 74,869.6 150,818.7 231,734.5 328,866.4

6211-3 Offices of Physicians, Dentists, and Other Health Practitioners

70,884.9 143,016.0 219,862.2 312,166.4

722 Food Services and Drinking Places

62,334.0 129,558.9 200,481.5 286,030.9

42 Wholesale Trade 59,532.3 127,261.3 197,840.2 283,054.9

491 Postal Service 33,358.6 91,388.9 148,249.3 218,343.0

5613 Employment Services 27,705.4 74,410.0 120,352.1 176,915.1

336412 Aircraft Engine and Engine Parts Manufacturing

26,375.5 73,267.3 119,088.9 175,619.9

72

Table 5-13. Top 10 Affected Industries for Airport Operations by Output in Orange County

NAICS Sector 2015 2020 2025 2030

4881 Support Activities for Air Transportation

2,468,768.9 6,860,690.8 11,152,054.3 16,446,525.1

Imputed Rental Activity for Owner-occupied Dwellings

147,573.5 311,143.8 483,832.2 693,333.6

492 Couriers and Messengers 100,185.9 276,623.5 449,242.0 662,135.0

531 Real Estate 101,320.4 233,049.6 367,433.7 530,932.5

622 Hospitals 91,991.1 191,146.5 295,804.3 422,076.3

5241 Insurance Carriers 66,834.4 156,005.0 246,926.5 357,971.1

6211-3 Offices of Physicians, Dentists, and Other Health Practitioners

72,957.5 151,797.2 235,013.6 335,467.3

42 Wholesale Trade 64,562.8 142,352.0 222,752.0 320,241.8

722 Food Services and Drinking Places

66,668.4 143,142.0 223,070.4 319,933.3

491 Postal Service 46,857.5 128,230.1 207,987.1 306,306.6

73

CHAPTER 6 CLUSTER ANALYSIS METHODOLOGY AND RESULTS

This chapter describes the methodology and results of the cluster analysis. It is the

third and final chapter that describes the analyses used to answer the research

questions. The purpose of this chapter is to identify possible industry clusters that

contribute to the economic impact.

Analysis Overview

A cluster is a “network of interrelated firms that buy and sell from the same

suppliers, share markets, and are supported by a common specialized infrastructure”

(Blakely & Leigh, 2010, p. 191). A cluster of firms may have an increased potential for

job creation and contribution to the success of the local economy. Airport operation is

the long-term and regular economic activity that will occur because of the initial

construction expenditure. Therefore, the purpose of the analysis is to identify possible

clusters of supporting industries in the area that may promote the continued success of

airport operations.

Clusters are generally defined by four characteristics: geographic concentration;

competitive advantage; supplier and buyer advantages; and advantageous

infrastructure (Blakely & Leigh, 2010; Blanco, 2010c). LQ, input-output and geographic

information system (GIS) data was used to help identify these possible clusters. The top

10 affected industry sectors of Orange County (Table 5-13) were used as a starting

point in identifying possible clusters. The industry sectors in those are most affected by

airport operations and therefore indicate specialized industry linkages necessary for a

cluster. Using this industry list, LQ data was acquired for each sector to verify its

competitive advantage (Table 6-1). As was mentioned in the previous chapter, the

74

‘Imputed Rental Activity for Owner-occupied Dwellings’ industry sector does not have a

corresponding NAICS code so this sector was not used in this analysis. GIS analysis

then was used to confirm both geographic concentration and physical proximity to

advantageous infrastructure. Not only must the firms be clustered near one another but

they also must be near advantageous infrastructure. For this analysis, the WOAA airport

was the advantageous infrastructure.

GIS data was acquired from the U.S. Census Bureau in the form of Longitudinal

Employer-Household Dynamics (LEHD) data. LEHD data provides employment figures

by census bock for each major industry sector. This data is available in tabular form and

was integrated with spatial data so that it may be analyzed using GIS processes.

Analysis Results

Table 6-1. LQ Values for Industries Most Affected by Airport Operations

Industry Orange County to Florida

Orange County to US

NAICS 42 Wholesale Trade 0.81 0.8

NAICS 491 Postal Service 2.40 1.54

NAICS 492 Couriers and Messengers 1.34 1.26

NAICS 524 Insurance Carriers and Related Activities

0.67 0.71

NAICS 531 Real Estate 1.27 1.85

NAICS 621 Ambulatory Health Care Services 0.68 0.77

NAICS 622 Hospitals 0.92 0.89

NAICS 722 Food Services and Drinking Places 0.96 1.05

Table 6-1 describes the LQ values for each of the most affected industries of

Orange County (except the ‘Support Activities for Air Transportation’ sector which is in

Table 4-3). Note the varying specificity of the industry sectors; this, as closely as

possible, represents the industry sector that is correlated to the IMPLAN sector. With

the goal of identifying industries that were specialized in the locality, industry sectors

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with LQ values greater than one (when compared to the state or nation) were selected

to be part of the GIS analysis. These sectors include: ‘Support Activities for Air

Transportation’; ‘Postal Service’; ‘Couriers and Messengers’; ‘Real Estate’; and ‘Food

Services and Drinking Places’.

Since the LEHD data was organized by census blocks, that unit was used as

areas of specialization. Note that LEHD industry data is limited to two NAICS codes of

specificity. For example, NAICS sector 72 ‘Accommodation and Food Services’ was

used to represent NAICS 722 ‘Food Services and Drinking Places’. All census blocks

with at least 10% of the total employment of each of the industry sectors was selected.

A total of six areas fit this criteria; one being within the SR 429 Extension Corridor

(Figure 6-1).

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Figure 6-1. Location of Potential Industry Clusters

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CHAPTER 7 DISCUSSION OF RESULTS

This chapter integrates the qualitative and quantitative results of the

methodologies of Chapters 4, 5 and 6. This is a holistic discussion of the available

findings to make conclusions that satisfy the research questions set forth in Chapter 1.

Support Activities for Air Transportation Sector

A healthy industry shows efficient economic linkages and the impressive

employment growth figures described in Table 4-1 gives the first indication that

investment in the ‘Support Activities for Air Transportation’ sector is justified. The LQ

values help substantiate this claim. Both values are greater than 1.0 so that indicates

healthy and possibly specialized local industries. The high 2.21 LQ value (when

compared to the nation) is an indicator of a strong, export base industry. That is, the

state and national ‘Support Activities for Air Transportation’ was strong enough to grow

in spite of major job losses in the state and national economies.

Despite these positives indications of a successful local industry, it’s necessary to

analyze the dynamism of the industry with the shift-share and Esteban-Marquillas

Extension analysis.

As was mentioned in Chapter 4, the negative total share values of the shift-share

analysis are expected and do not reflect negatively on the local industry. In fact, positive

mix shift values were complimented by the negative total share values. These values

indicate that the ‘Support Activities for Air Transportation’ industry sector at the

reference economy level experienced an employment growth while the overall

economies were in decline. It is a good sign that the national and state ‘Support

Activities for Transportation’ sectors are growing because it dispels a possible

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reservation in investing in a local industry that is failing at the higher levels. The positive

competitive shift values provide indications of a healthy local industry, especially since

the mix shift values were also positive. In summary, the shift share values (when

compared to the nation) suggest that though the overall national economy was in

decline from 2005 to 2010, the national ‘Support Activities for Air Transportation’

industry was growing. More importantly, the Orange County ‘Support Activities for Air

Transportation’ industry sector was growing at a faster rate that the increasing national

industry sector. The same can also be said about the shift share values when compared

to the state: the local ‘Support Activities for Air Transportation’ industry sector was

growing faster at the local level when compared to the state industry, also growing in a

declining overall state economy.

The Esteban-Marquillas Extension analysis is where the indications of industry

health presented by the results of the LQ and shift-share are confirmed. The high LQ

value (when compared to the nation) insinuated that the local industry was specialized

and indeed it is. The positive specialization value of the Esteban-Marquillas Extension

did indicate that the local industry is specialized, when compared to the nation. The LQ

value for the state comparison (1.18) was not as high as the national comparison (2.21)

but it did not rule out the possibility of the local industry being specialized when

compared to the state. However, the negative specialization measure when the local

industry is compared to the state reveals that the local industry is not specialized.

Though the local industry appears to be specialized when compared to the United

States and not specialized when compared to Florida, the comparative advantage

values both tell the same story. Whether compared to the state or nation, the ‘Support

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Activities for Air Transportation’ sector in Orange County is positive and indicates a

comparative advantage. The positive competitive shift values of the shift-share analysis

also alluded to this conclusion. Therefore, the magnitude of the comparative advantage

and specialization effect values indicate that the local industry markets were functioning

normally when compared to the nation but not functioning normally when compared to

the state. This means that the local industry is healthy and intervention is unnecessary

when compared to the nation but local industry may require public intervention to better

its health.

In summary, the overall results of the LQ, shift-share, and Esteban-Marquillas

analyses signify that the ‘Support Activities for Air Transportation’ industry sector is

healthy, in relation to state and national standards. This conclusion is made despite the

fact that the LQ does not meet the requirements for an export base industry or the

requirements to be considered specialized, by state standards. It is important to note

that the LQ was positive and near the point where it could be declared an export base

industry. So it is not to say that the state compared LQ value does not indicate that

there would be positive economic impacts. Also, the state shift-share analysis provided

similarly positive results to the national comparison. The relatively subpar, state

compared specialization effect is most likely a result of the state’s industry specialization

in relation to the national economy. A LQ calculation on the industry at the state level

compared to the national level proves this (LQ = 1.86). So it is not to say that the local

industry seemed unhealthy or uncompetitive by state standards. Furthermore, the

conclusions that can be made by national comparisons supersede any disparities

between state and local comparisons. The state of Florida and its economy is, after all,

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a part of the United States and the national economy. Therefore, public investment in

this local industry is justified because further growth would benefit the overall local

economy.

Nonscheduled Air Transportation Sector

After concluding there is justification for public investment in the local ‘Support

Activities for Air Transportation’, it is important to analyze the economics of what this

researcher believes will be the most affected industry. As was mentioned in Chapter 4,

the two LQ values provide seemingly contradicting conclusions. When compared to the

nation it seems like the local industry is not only healthy but also an export industry. In

contrast, when compared to the state the local industry is does not meet the need of the

locality. This large disparity is best explained by with the same rationale used in the

previous section. The ‘Nonscheduled Air Transportation’ industry at the state level has a

proportionally higher employment than the nation. The calculation of the LQ for this

industry at the state level compared to the national proves this (LQ = 1.58). Therefore,

when the local industry is compared to the state, it seems like the local industry is not

healthy. Therefore, the overall conclusion is that the local industry is healthy and does

represent an export industry, but it is subpar within the overachieving state economy.

The values of the shift-share analysis indicate that the ‘Nonscheduled Air

Transportation’ industry was relatively unhealthy at the national and local level from

2005 to 2010. The national industry sector was riveted with steep employment decline

and the local industry sector experienced even steeper decline when compared to the

nation. At the state level, however, the state industry sector showed signs of growth but

the local industry sector (when compared to the state) showed the same declining trend

as it did when compared to the nation.

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The Esteban-Marquillas results confirm the conclusions of the LQ and shift-share

analysis. Both (compared to the state and nation) the state and nationally compared

specialization effects were positive, indicating a specialized local industry sector. As

was suggested by the shift-share analysis, the negative comparative advantage values

confirm that the local industry sector does not have an advantage over the state or

national economies. This endorses the conclusion that indirect investment in the local

‘Nonscheduled Air Transportation’ sector may have substantial positive impacts but

does not confirm this effect.

A relative conclusion can be made by looking at Table 5-1. With the

‘Nonscheduled Air Transportation’ industry sector sporting the lowest multiplier

coefficients in the table, it can be concluded that the sector will have a relatively minimal

economic impact. That said, the IMPLAN models determines that neither

‘Nonscheduled Air Transportation’ nor any air transportation related sectors were

among in the top 10 most affected industries by investment in airport operations. This is

likely the case because many of the most affected industries are those that provide

inputs necessary to operate an airport; especially personnel related costs and the

induced impacts.

Economic Impacts

The construction related activities will be the recipient of the $10’s of millions of

direct government investment so this investment will clearly have more profound

impacts than those of the airport operation activities. With a direct investment of $49.7

million, the IMPLAN software estimates that more than $70.2 million would be circulated

throughout the SR 429 Extension Corridor. The effects would reach an estimated $82.5

million in Orange County. With the larger study area, the absolute effects are greater as

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there are more opportunities for the ripples of the economic investment to ripple through

the area.

The construction effort would directly support 372 jobs. An additional 174 local

jobs will be supported, if the impact growth were limited to the SR 429 Extension

Corridor. These employment figures would be slightly larger when Orange County is

used as the study area. An estimated 386 direct jobs and an additional 265 local jobs

would be supported in Orange County. These are positive figures for a state that has

the highest rate of long-term unemployment in the nation (Luhby, 2012). It is important

to note that these employment figures do not represent annual employment but rather a

temporary boost. The direct investment in airport construction is a one-time expenditure.

Therefore the project would not sustain these jobs once the construction is complete.

Skeptics may say that a $50 million investment is not worth the 651 jobs but it is

important to remember that this is an investment in transportation infrastructure.

Transportation infrastructure is usually very capital intensive but the impacts cannot

simply be measured in the number of jobs created but the immeasurable impact of the

increased accessibility and mobility. Increased mobility and accessibility allow for the

more efficient movement of people and goods and this impact is very difficult to

measure.

Sustained employment opportunities would be expected from the continued

operation the airport, unlike employment related to construction activities. Estimates

provided on Figure A-1 indicate that the airport is expected in increase its annual

employment by 30 people every five years; with 34 in 2015 and 124 in 2030. This

represents an annual 18% increase in direct effect jobs from 2015 to 2030. In the SR

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429 Extension Corridor, total jobs are expected to climb from 44 in 2015 to 175 in 2030;

representing an annual growth of 20%. In Orange County, an annual job increase of

21% is expected.

From 2015 to 2030, direct airport expenditures are expected to increase by an

average annual rate of 62%. With direct airport expenditures in the SR 429 Extension

Corridor being increased 1.45 times, the total economic output is expected to grow from

nearly four million dollars in 2015 to $36.9 million in 2030. This results in a total growth

of 829% (55% annually) of total output. In Orange County, the total output growth

average will be 839% (56% annually) as total output increases from $4.8 million in 2015

to $43.9 million in 2030. The initial public investment of $49.7 million will establish a firm

in Orange County that will create $43.9 million of annual economic impact by 2030.

Most Affected Industries

As was mentioned earlier, it is surprising that none of the air transportation

industry sectors are not represented in the top 10 most affected industries by airport

operations. The ‘Postal Service’, ‘Employment Service’ and ‘Aircraft Engine Parts

Manufacturing’ are most affected by indirect effects, when the SR 429 Extension

Corridor is the study area. With the presence of the aerospace giant, Lockheed Martin,

in Orange County perhaps this is adds to reason that ‘Aircraft Engine Parts

Manufacturing’ is among the most industries most affected by airport operations in

Orange County.

Two of the industry sectors in Orange County are particularly specialized in

indirect effects – ‘Support Activities for Air Transportation’ sector – ‘Postal Service’ and

‘Couriers and Messengers’. These sectors all have higher indirect impact values than

induced impact vales. This indicates that they are primarily affected by the products and

84

services that they will sell to support the ‘Support Activities for Air Transportation’

sector. When the induced impact values are greater than the induced impact values,

this indicates that these industry sectors are mostly supported by the economic activity

of personal spending. This is true for the remaining industries on the list; none of which

was much of a surprise. The effect on the ‘Real Estate Establishments’ sector was

nearly evenly split between indirect and induced industry sectors for all scenarios. This

perhaps indicates that the aerotropolis or airport city concept would be in effect in the

area – airports are increasingly getting into the business of land acquisition and

development.

Clustered Industries

Applying the concept of cluster analysis helped justify investment in airport

development. If firms from each of the most affected industry sectors are located near

one another, then they are more likely to have profound and continued economic effects

on airport operations. They allow the efficient exchange of goods and services of

interrelated industries, essentially forming symbiotic relationships. Clustered industries

benefit one another and also the locality as sustained economic success is often an

outcome.

The presence of clusters may support the success of the WOAA airport. Potential

supporting industry clusters were identified if they met the qualifications. Six resulting

census blocks met the criteria of the cluster analysis; however, one census block in

particular seemed especially apt to host supporting industry clusters. This is because of

its location within the SR429 Extension Corridor and proximity to the WOAA site.

Census Block 1018 was the only potential cluster than was located within the SR 429

Extension Corridor and it is located about five miles east of the WOAA area which

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makes it the closest. Its proximity to the proposed airport makes it an attractive site for

supporting industry clustering, therefore increasing the potential of that this cluster will

further the economic impact.

Summary

In this chapter, a discussion of the results justified the public investment in the

WOAA airport. The ‘Support Activities for Air Transportation’ industry is healthy and

further growth will create a ripple effect in the local economy, creating further economic

growth. As was indicated by the economic base analyses, substantial impacts will be

the result of the construction and annual operation of the airport. For every dollar spent

during the construction phase, $1.63 of economic impact would be felt in Orange

County. Even better, for every one dollar spent in operating the airport $1.70 will be

circulated throughout the county. Development and operation of the expanded airport

does serve the greater good because of the economic impacts. Impacts will be felt

throughout the county in a number of different industry sectors. Though this is a facility

that will only directly be used by a small portion of the population, it is an investment in

transportation infrastructure that increases the capacity for aviation activity in Orange

County. As was discussed in Chapter 2, airport efficiency is important because aviation

activity is an integral aspect of modern economic activity.

Despite the research hypothesis, ‘Nonscheduled Air Transportation’ was not

among one of the most affected industries. Luckily, a cluster analysis of the most

affected industry shows that there are six potential sites of industry clustering in Orange

County. Clustering will only serve to increase the local economic impact of airport

operations; further justifying the large public investment.

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CHAPTER 8 CONCLUSION

Recommendations

Looking at the proposed airport development concepts, this researcher

recommends that the first implementation concept is chosen for implementation. There

are more positives with this concept than the other concept plans; namely the location

of the airport. Orlando Apopka Airport is the largest of the three airports in the WOAA

study area. It also has the most comprehensive existing infrastructure which should

lower cost of development. Its adjacency to US 441 is another plus that the other two

facilities lack. The proximity to this major arterial would provide greater access, allowing

it to become the multimodal hub that officials hope for. Furthermore, it is the closest in

proximity to the potential industry cluster identified in Census Block 1018. However, it

may be more expensive to develop because of specific site conditions that would

increase the cost of development.

This researcher would also like to recommend that the economic incentives and

be provided for clustered industries. The presence of clustered industries creates further

economic prosperity and helps to maintain economic sustainability in a region. Six

potential sites of clustered industries were identified in Chapter 6. So this, perhaps,

provides a good starting point for that recommendation.

Limitations

A number of data limitations presented themselves during the course of this

research. Most notably was the lack of availability of more recent employment data. The

BLS only provided data from 2010 as the most recently available data. Newer data

would allow for more accurate economic base analyses. As it stands, the data was

87

nearly two years old at time of analysis. Another source of data limitations is with the

IMPLAN data. The exorbitant cost of data and release date inconveniences resulted in

the use of 2009 IMPLAN data. It is not clear if much would have changed in the data if

the more up-to-date 2010 was used but 2009 was deemed to be acceptable due to the

limitations.

It is important to remember that the economic base analysis used in this research

do not describe the economic trends of particular firms in Orange County. That is, it

does not report the trends of any particular airport but rather the industry as a whole in

Orange County. The presence of Orlando International Airport in Orange County is

likely to significantly impact on the results of the economic base analysis. This is not to

say that the results are inaccurate but rather should not be misinterpreted as the

employment trends of any airport in particular. This is a limitation of the economic base

analysis.

Opportunities for Future Research

Though this research is a comprehensive analysis, opportunities exist to take what

was started here and expand it to include more scenarios and possibilities. The

research questions presented in Chapter 1 focused only on the specific economic

activity of airport operations. WOAA plans for a multimodal hub with a number of other

commercial and industrial activities occurring on the site. The incorporation of these

supporting activities will only serve to make the WOAA airport more successful and

prosperous. Future research may account for these additional activities and estimate

their local economic impacts.

Due to cost of the input-output data, the study area for these analyses was limited

to Orange County. With additional input-output data, the study area could be expended

88

to include other counties in the region or even the state. This research project looked at

the economic impact on a finite scale. But in reality, effects of economic activity do not

stop at county lines and other jurisdictions. It would be worth analyzing the impacts at

larger scales.

Final Thoughts

It is important to remember that the economic base analysis illustrates industry

trends for Orange County. While this is a good analysis to understand the economic

trends when compared to the base economies, there is an unmeasured dynamism

within Orange County. There are 29 airport facilities within the county and it is safe to

assume that the expansion of a WOAA airport will shift aviation activity within the

county. Also the results of the economic base analysis may be overstated because of

the presence of Orlando International Airport. As mentioned earlier, Orlando

International Airport is one of the busiest airports in the nation.

Competition from Orlando International Airport should not pose much negative

impact on the WOAA airport. Orlando International Airport serves primarily as a

commercial airport while the WOAA airport serves as a general aviation airport. Though

general aviation activities are permitted and do occur at Orlando International Airport, it

will not be a direct competitor to the WOAA airport. The improved WOAA airport

infrastructure will make it a more attractive destination than Orlando International Airport

for general aviation activities. The new and improved runways increases accessibility as

it will be able to accommodate a wider variety of aircraft. The WOAA will also be less

congested than Orlando International Airport. A less congested airport makes landings

and takeoffs more time efficient, which also makes it a more attractive option. This

89

researcher believes that the WOAA airport will be the benefactor of a shift of general

aviation activities from some of the larger and busier airports in the county.

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APPENDIX A PROJECTED AIRPORT CONSTRUCTION AND OPERATIONAL BUDGETS

The following tables are part of the WOAA feasibility plan. They depict the

budgetary cost assumptions for development and annual operation from through 2030.

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Table A-1. Preliminary Cost Estimate of Total Project and Phasing

Project Phasing and Costs Phase Project Percentages Amounts

2010 Cost FAA FDOT Local FAA FDOT Local

1EA 252,000 95.0% 2.5% 2.5% 239,400 6,300 6,300

1 DR I/ADA 630,000 95.0% 2.5% 2.5% 598,500 15,750 15,750

1 Airport Master Plan 220,500 95.0% 2.5% 2.5% 209,475 5,513 5,513

1 Master Drainage Plan and Master Permitting 289,800 95.0% 2.5% 2.5% 273,310 7,245 7,245 Phase 1 Total 1,392,300

1,322,685 34,958 34,958

2 Environmental Mitigation 3,400,000 95.0% 2.5% 2.5% 3,230,000 85,000 85,000

2 Land Acquisition 7,700,000 95.0% 2.5% 2.5% 7,315,000 192,500 192,500

2 Construct R/W 6,930,000 95.0% 2.5% 2.5% 6,583,500 173,250 173,250

2 Construct R/W Safety Areas 630,000 95.0% 2.5% 2.5% 598,500 15,750 15,750

2 Construct Apron 1,638,000 95.0% 2.5% 2.5% 1,556,100 40,950 40,950

2 Construct Connector T/W 252,000 95.0% 2.5% 2.5% 239,400 6,300 6,300

2 Drainage System and Retention Ponds 1,890,000 95.0% 2.5% 2.5% 1,795,500 47,250 47,250

2 Terminal Building 945,000 0.0% 50.0% 50.0% - 472,500 472,500

2 Automobile Parking 40 252,000 0.0% 50.0% 50.0% - 126,000 126,000

2 FBO Hangar 630,000 0.0% 50.0% 50.0% - 315,000 315,000

2 Lighting MIRLS 441,000 95.0% 2.5% 2.5% 418,950 11,025 11,025

2 Lighting MITLS 252,000 95.0% 2.5% 2.5% 239,400 6,300 6,300

2 Lighting Apron 189,000 95.0% 2.5% 2.5% 179,550 4,725 4,725

2 Lighting Auto Parking 94,500 95.0% 2.5% 2.5% 89,775 2,363 2,363

2 Electrical Vault 189,000 95.0% 2.5% 2.5% 179,550 4,725 4,725

2 Sewer and Water 315,000 0.0% 50.0% 50.0% - 157,500 157,500

2 Electrical Service Lines 126,000 0.0% 50.0% 50.0% - 63,000 63,000

2 Access Road 504,000 0.0% 50.0% 50.0% - 252,000 252,000

2 Engineering (1) 2,283,750 80.0% 10.0% 10.0% 1,827,000 228,375 228,375

2 Contingency (2) 4,026,125 85.0% 7.5% 7.5% 3,422,206 301,959 301,959 Phase 2 Total 42,627,375

37,117,431 2,754,972 2,754,972

Source: Orlando Aviation Consultants, 2011

(1) Engineering is assumed to be 10% of total excluding land acquisition (2) Contingency is assumed to be 10% of total including engineering cost

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Table A-1. Preliminary Cost Estimate of Total Project and Phasing (continued)

Project Phasing and Costs Phase Project Percentages Amounts

2010 Cost FAA FDOT Local FAA FDOT Local

3 Construct Parallel T/W 2,646,000 95.0% 2.5% 2.5% 2,513,700 66,150 66,150

3 Drainage System and Retention Ponds 1,890,000 95.0% 2.5% 2.5% 1,795,500 47,250 47,250

3 T-Hangars 30 378,000 0.0% 50.0% 50.0% - 189,000 189,000

3 Sewer and Water 126,000 0.0% 50.0% 50.0% - 63,000 63,000


3 Industrial Park Roads 252,000 0.0% 50.0% 50.0%

126,000 126,000

3 Engineering (1) 534,240 76.4% 12.0% 12.0% 406,022 64,108 64,108 3 Contingency (2) 587,664 76.4% 12.0% 12.0% 446,625 70,519 70,519

Phase 3 Total 6,464,304

5,161,847 651,227 651,227

4 T-Hangars 30 378,000 0.0% 50.0% 50.0% - 189,000 189,000

4 Sewer and Water 31,500 0.0% 50.0% 50.0% - 15,750 15,750


4 Engineering (1) 42,210 0.0% 50.0% 50.0% - 21,105 21,105 4 Contingency (2) 46,431 0.0% 50.0% 50.0% - 23,216 23,216

Phase 4 Total 510,741

255,371 255,371

5 T-Hangars 30 378,000 0.0% 50.0% 50.0%

189,000 189,000

5 Land Acquisition for R/W extension 3,307,500 95.0% 2.5% 2.5% 3,142,125 82,687 82,687

5 RW ext 1,638,000 95.0% 2.5% 2.5% 1,556,100 40,950 40,950

5 Construction R/W Safety Area 315,000 95.0% 2.5% 2.5% 299,250 7,875 7,875

5 Parallel TW ext 630,000 95.0% 2.5% 2.5% 598,500 15,750 15,750

5 LPV approach 500,000 95.0% 2.5% 2.5% 475,000 12,500 12,500

5 Sewer and Water 63,000 0.0% 50.0% 50.0% - 31,500 31,500


5 Industrial Park Roads 252,000 0.0% 0.0% 100.0% - - 252,000

5 Industrial Park Utilities (electrical and water) 88,200 0.0% 0.0% 100.0% - - 88,200

5 Engineering (1) 527,940 76.3% 12.0% 12.0% 401,234 63,352 63,352

5 Contingency (2) 911,484 80.0% 10.0% 10.0% 729,187 91,148 91,148

Phase 5 Total 8,636,324

7,201,396 547,364 887,564

Project Total - All Phases 59,631,044

50,803,359 4,273,893 4,584,092


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Table A-2. Abridged Near Term and Long Term Operation Revenue/Cost Estimates With Assumptions

2015 2020 2025 2030

REVENUE

Tie Down Fees 261,966 459,602 704,655 1,006,176

Fuel 49,075 79,037 127,289 205,000

Lease Income Aviation Use 2,579,611 5,798,793 8,146,677 9,217,217

Professional Office Space 182,500 1,301,119 2,208,146 2,498,314

Retail 150,000 848,556 960,063 1,086,224

Industrial Space 400,000 5,430,759 14,848,981 32,441,879

Miscellaneous Income 638 814 1,039 1,327

TOTAL REVENUE 3,613,791 13,918,671 26,996,851 46,456,137

OPERATING EXPENSES

Advertising (2% of Revenue) 72,276 278,373 539,937 929,123

Bank Charges 200 300 400 500

Contract Labor 7,730 12,450 20,051 32,292

Depreciation (S/L for 29.5 yrs) 896,324 5,100,275 10,443,660 18,888,078

Dues & Subscriptions 460 560 660 760

Employee Benefits 55,769 102,012 161,571 237,515

Insurance (2.7% of Revenue) 97,572 375,804 728,915 1,254,316

Office Expense 5,100 6,600 8,100 9,600

Outside Services 22,973 29,320 37,421 47,759

Payroll-Administration & Operations 1,394,215 2,550,300 4,039,284 5,937,884

Payroll Taxes 121,994 223,151 353,437 519,565

Permits & Fees 1,700 2,200 2,700 3,200

Postage & Delivery 580 640 707 780

Professional Services 22,973 29,320 37,421 47,759

Repairs & Maintenance 3,063 3,909 4,989 6,368

Supplies 1,532 1,955 2,495 3,184

Telephone 10,433 12,095 14,022 16,255

Utilities 6,414 7,617 9,047 10,745

TOTAL OPERATING EXPENSES 2,721,308 8,736,882 16,404,816 27,945,684

OPERATING INCOME 892,483 5,181,789 10,592,034 18,510,454

OTHER EXPENSES

Interest on Acquisition & Build out 1,024,247 4,744,743 9,473,640 16,946,949

NET OPERATING INCOME -131,764 437,045 1,118,395 1,563,505


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APPENDIX B NAICS INDUSTRY SECTOR DEFINITIONS

4812 Nonscheduled Air Transportation 48121 Nonscheduled Air Transportation This industry comprises establishments primarily engaged in (1) providing air transportation of passengers and/or cargo with no regular routes and regular schedules or (2) providing specialty flying services with no regular routes and regular schedules using general purpose aircraft. These establishments have more flexibility with respect to choice of airports, hours of operation, load factors, and similar operational characteristics. Illustrative Examples: Air taxi services Nonscheduled air freight transportation services Aircraft charter services Nonscheduled air passenger transportation services 481211 Nonscheduled Chartered Passenger Air Transportation US This U.S. industry comprises establishments primarily engaged in providing air transportation of passengers or passengers and cargo with no regular routes and regular schedules. 481212 Nonscheduled Chartered Freight Air Transportation US This U.S. industry comprises establishments primarily engaged in providing air transportation of cargo without transporting passengers with no regular routes and regular schedules. 481219 Other Nonscheduled Air Transportation US This U.S. industry comprises establishments primarily engaged in providing air transportation with no regular routes and regular schedules (except nonscheduled chartered passenger and/or cargo air transportation). These establishments provide a variety of specialty air transportation or flying services based on individual customer needs using general purpose aircraft. Illustrative Examples: Aircraft charter services (i.e., general purpose aircraft used for a variety of specialty air and flying services) Aviation clubs providing a variety of air transportation activities to the general public

4881 Support Activities for Air Transportation This industry group comprises establishments primarily engaged in providing services to the air transportation industry. These services include airport operation, servicing, repairing (except factory conversion and overhaul of aircraft), maintaining and storing aircraft, and ferrying aircraft. 48811 Airport Operations

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This industry comprises establishments primarily engaged in (1) operating international, national, or civil airports or public flying fields or (2) supporting airport operations (except special food services contractors), such as rental of hangar space, air traffic control services, baggage handling services, and cargo handling services. 488111 Air Traffic Control This U.S. industry comprises establishments primarily engaged in providing air traffic control services to regulate the flow of air traffic. 488119 Other Airport Operations CAN This U.S. industry comprises establishments primarily engaged in (1) operating international, national, or civil airports, or public flying fields or (2) supporting airport operations, such as rental of hangar space, and providing baggage handling and/or cargo handling services. 48819 Other Support Activities for Air Transportation See industry description for 488190 below. 488190 Other Support Activities for Air Transportation This industry comprises establishments primarily engaged in providing specialized services for air transportation (except air traffic control and other airport operations). Illustrative Examples: Aircraft maintenance and repair services (except factory conversions, overhauls, rebuilding) Aircraft testing services

Source: U.S. Census Bureau, 2011a

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BIOGRAPHICAL SKETCH

Gareth Reece Hanley was born on the small island of St. Kitts in the Caribbean.

When he was five, his family immigrated to the United States so that he and his two

siblings would have greater educational opportunities. After earning a Bachelor of

Science degree in geography from the University of Florida, he decided to pursue a

Master of Arts in Urban and Regional Planning. Already with an interest in

transportation planning, he discovered he was also interested in the role economics

plays in planning. He selected a thesis topic by integrating his long-time passion for

aviation with his interests in transportation and economics planning.

Documents

To my parents, for all they sacrificed to provide me the … · 2012-10-04 · 4 ACKNOWLEDGMENTS First and foremost, I thank my chair, Dr. Andres Blanco, for inspiring me to think